A Technological Wiki - User contributions [en]

Training report

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Whenever somebody takes a training lesson, it is recommended to generate a report of this training in order to transmit the knowledge to the rest of the colleagues. Trainings can be from a presential conference, online, a book or even another website.


= Guideline =


== Title ==

Title of the training


== TL:DR; (Too Long: didn't read) ==

short summary and conclusions of the training

== description ==

Detailed information about the training

== sources ==

Where the information has been obtained from


= document info =

* Name
* email
* Department
* Position

Request For Comments

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An RFC, or "Request for Comments" is a type of publication from the technical communities. These documents are a series of numbered memos proposing new standards, protocols, procedures, and processes. Originally, RFCs were literally "requests for comments" and were used to solicit input. Over time, the term has been retained, but many RFCs now represent established standards.

While some RFCs are purely informational, others represent consensus on best practices or standards. When an RFC describes a standard, it goes through review and approval process before being published. This ensures that the standard is technically sound and meets the companies' needs.


= Purpose of RFC =

* '''Standards Track''': Specifies protocol standards and best current practices.
* '''Informational''': Describes a topic without any standardization intent.
* '''Experimental''': Details an experiment. It doesn't necessarily mean that it will become a standard in the future.
* '''Historic''': Marks a previous standard that has been made obsolete or that was never standardized.


= RFC structure =

* '''Introduction''': overview of the topic, setting context, and providing a brief on the subject matter.
* '''Motivation''': reasons prompting the proposal, underlying issues with current systems, and the need for change.
* '''Features''': specific attributes, functionalities, or characteristics of the proposed solution or product.
* '''Expected benefits''': positive outcomes, advantages, or value-added results from implementing the proposal.
* '''Implementation plan''': step-by-step approach, timeline, and phases for rolling out the proposal or solution.
* '''Concerns & risks''': potential challenges, pitfalls, or negative outcomes that might arise from the proposal.
* '''Feedback requested''': request for opinions, suggestions, and thoughts from stakeholders to refine the proposal.


= RFC example of implementation of new customer service software - "HelpMasterPro" =


== Introduction ==

We propose the adoption of a new customer service software solution, "HelpMasterPro", to enhance our customer support efficiency, improve ticket resolution times, and provide better analytics.


== Motivation ==

Our current software, "OldSupportSoft", has been in use for 5 years. It lacks modern features, has scaling issues, and doesn't integrate well with our other systems.


== Features of HelpMasterPro ==

* Omnichannel support (email, chat, phone)
* Integrated knowledge base
* Advanced analytics and reporting
* Seamless integration with our CRM
* AI-driven auto-responses


== Expected benefits ==

* Reduction in ticket response time by 30%
* Improved customer satisfaction scores
* Enhanced productivity of our support agents
* Data-driven decision-making


== Implementation plan ==

* Phase 1: Software procurement and initial setup (2 weeks).
* Phase 2: Training for customer service representatives (1 week).
* Phase 3: Migration from "OldSupportSoft" (3 weeks).
* Phase 4: Full launch and decommissioning of "OldSupportSoft" (1 week).


== Concerns & risks ==

* Downtime during migration.
* Training requirements for staff.
* Potential integration issues with our CRM.


== Feedback requested ==

* Do you foresee any challenges with the proposed software?
* Are there features in "OldSupportSoft" you think we should retain?
* How can we minimize disruption during the transition?


[[Category:documentation templates]]

Request For Comments

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Post Mortem

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A post mortem refers to a retrospective analysis or discussion conducted at the conclusion of a project or after an event has occurred. Its primary goal is to evaluate and understand the successes and failures of the project or event. Participants discuss what went well, what could have been improved, and lessons learned. This process helps teams identify best practices for future endeavors and pinpoint areas for improvement. By examining both the positive and negative aspects of the project's lifecycle, teams can prevent repeated mistakes and continuously refine their processes.

Post mortem and the "5 Whys" methodology are both analytical tools used to understand failures or problems. A post mortem is a retrospective analysis conducted after a project or event has concluded to determine what went well and what went wrong. It aims to identify learnings and improvements for future endeavors. On the other hand, the "5 Whys" methodology is a root cause analysis tool that asks "why?" five times (or as many times as needed) to drill down into the source of a specific problem. Instead of a broad overview, it seeks to understand the fundamental cause of a single issue, ensuring the same mistake isn't repeated.

== objectives ==

* find the root of the problem
* set mechanisms to avoid happening again
* accept the failure and not blame the final responsible
* generate a report of what has happened.

-----


= Guideline =


== Preparation ==

* '''Schedule the meeting''': Ensure that all key stakeholders can attend.
* '''Gather data''': Before the meeting, collect all relevant data and statistics related to the project or event.
* '''Set the ground rules''': Make it clear that the post-mortem is a blame-free environment. This is about learning and growing, not pointing fingers.


== Begin the Meeting ==

* '''State the objective''': Remind participants that the goal is to learn and improve.
* '''Review the project''': Briefly go over the goals, timelines, and key metrics of the project.


== Discuss What Went Well ==

* '''Successes''': Identify all the things that went according to plan or exceeded expectations.
* '''Contributing factors''': Discuss why these aspects of the project were successful.


== Discuss what didn't go well ==

* '''Challenges''': Identify the obstacles and problems that arose during the project.
* '''Root causes''': Delve into why these challenges occurred. Was it due to inadequate resources, miscommunication, technical failures, etc.?


== Recommendations for Improvement ==

* '''Solutions''': For each problem identified, discuss potential solutions or changes that can prevent it in the future.
* '''New processes''': Identify any processes or methods that can be introduced to improve future projects.


== Action Items ==

* '''Assign responsibility''': For each recommendation, assign a responsible person or team to take it forward.
* '''Set deadlines''': Establish a timeline for when the recommendations should be implemented.


== Feedback on the Post-Mortem Process ==

Ask participants for feedback on the post-mortem process itself. Is there anything that can be improved for next time?


== Documentation ==

* '''Compile findings''': Document everything discussed during the post-mortem, including successes, challenges, recommendations, and action items.
* '''Distribute''': Share the post-mortem report with all stakeholders, and consider storing it in a central location where team members can refer to it in the future.


== Follow up ==

* '''Monitor implementation''': Ensure that the recommended action items are being implemented.
* '''Check-in''': A few weeks or months down the line, revisit the action items to see if they've had the desired impact.


[[Category:documentation templates]]

Post Mortem

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Architectural Decision Record

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ADR, or Architectural Decision Record, is a concise record of architectural decisions made during the software design process. These records capture the context in which the decision was made, the decision itself, and the consequences of the decision. ADRs should be written whenever a decision has been made that affects the system's architecture, its non-functional requirements, or its development processes. Note that not every change requires an ADR. The intent is to capture meaningful decisions that have a lasting impact on the project or system. If the decision would benefit from additional context or if future developers might wonder 'why was this done?', then it's worth capturing in an ADR. Also, keep in mind that ADRs aren't set in stone. As systems evolve and requirements change, previous architectural decisions might be revisited, and new ADRs can be created to document the evolution.


== Case scenarios ==

* '''Significant architectural changes''': whenever a decision is made that significantly changes the system's architecture, such as adopting a microservices architecture, choosing a specific database system, or introducing a new technology stack.
* '''New Requirements''': when new business or technical requirements lead to architectural changes. For example, a requirement for multi-region support might necessitate decisions around data replication and latency.
* '''Trade-offs''': anytime there are multiple options considered and trade-offs evaluated to make a decision. Documenting why certain options were rejected can be as valuable as documenting why one was chosen.
* '''Risk mitigation''': when a decision is made to address risks, such as security vulnerabilities or potential bottlenecks in the system, it's beneficial to capture the decision and the context.
* '''Changes to established practices''': if the development or deployment practices are changed, such as adopting a new branching strategy or incorporating new CI/CD tools.
* '''Overturning previous decisions''': when an earlier decision is being revisited, modified, or reversed, an ADR can provide insight into what's changed in the interim, be it new information, shifting requirements, or the evolution of technology.
* '''Regulatory or compliance impacts''': in industries where regulatory or compliance requirements are crucial, architectural decisions made to meet these requirements should be documented.
* '''Knowledge sharing''': to ensure that team members, especially those who join later in the project, understand the context and rationale behind certain choices.
* '''Controversial decisions''': when the team is divided on a particular decision or when it could have significant consequences (either positive or negative).


== ADR structure ==

* '''Title''': short present-tense phrase or sentence explaining the decision.
* '''Status''': proposed, Accepted, Rejected, Superseded, etc.
* '''Date''': date of last edition of document
* '''Participants''': colleagues involved on creating the document.
* '''Context''': describes the situation, constraints, or problem leading up to the decision.
* '''discussion''': defines all the brainstorming that has been made to find a way to solve the problem.
* '''Decision''': a concise description of the chosen solution or strategy.
* '''Consequences''': describes the outcomes, changes, and impacts resulting from the decision.


== Example ADR of starting to use Docker ==


=== Title ===

Adoption of docker for microservices deployment


=== Status ===

Accepted


=== Date ===

2022-08-27


=== Participants ===

* Jane Doe (Lead Architect)
* John Smith (DevOps Engineer)
* Emily Clark (Backend Developer)


=== Context ===

As our application grows in complexity, the team has been exploring ways to simplify deployment, improve scalability, and isolate service failures. We've identified that adopting a microservices architecture might address our concerns. However, deploying microservices can be complicated due to the management of multiple small services, each with its own dependencies.


=== Discussion ===

* '''Option 1''': Traditional VMs
** '''Pros''': Well-understood, isolation at the OS level.
** '''Cons''': Resource-heavy, slower to start, managing multiple VM images can become tedious.
* '''Option 2''': Docker containers
** '''Pros''': Lightweight, fast startup, isolation at the process level, consistent environments.
** '''Cons''': Requires new knowledge and tooling, potential security concerns if not configured properly.
* '''Option 3''': Serverless functions
** '''Pros''': Fully managed, auto-scaling, pay-as-you-go.
** '''Cons''': Might not suit all types of microservices, cold starts, vendor lock-in.

The team leaned towards Docker due to its lightweight nature, the vast community and ecosystem, and its ability to ensure consistent environments across different stages of development and deployment.


=== Decision ===

Adopt Docker for deploying our microservices. We'll containerize each service with its dependencies, ensuring a consistent environment from development to production. Additionally, we'll invest in tooling (like Docker Compose for local development and Kubernetes for production) to manage these containers.


=== Consequences ===

* All microservices will be developed with Docker in mind, possibly requiring some refactoring of existing services.
* Team members will need training on Docker, and potentially Kubernetes, to understand best practices and security considerations.
* While initial setup might increase development time, we expect faster deployment cycles and increased system stability in the long run.
* We will need to monitor the system closely initially to ensure there are no unforeseen issues with container orchestration, especially under heavy loads.

The team will need training since Cassandra and NoSQL approaches differ from traditional RDBMS. We'll need to design our data models differently, considering denormalization and Cassandra's query-first design principle. Given Cassandra's eventual consistency model, we might experience some consistency-related challenges, but this is a trade-off we're willing to make for the scale and availability it offers.


[[Category:documentation templates]]

Architectural Decision Record

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5 whys

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The "5 Whys" is a problem-solving methodology that focuses on identifying the root cause of an issue by asking "Why?" repeatedly until the underlying problem is identified. It is a straightforward technique developed by Sakichi Toyoda and was later integrated into the Toyota Production System. Although it's called the "5 Whys," it's not strictly limited to five questions; you keep asking "Why?" until you reach the root cause.


= Procedure =

* State the problem clearly.
* Ask "Why did this problem occur?"
* Based on the answer to the first "Why?", ask "Why?" again.
* Continue the process until you identify the root cause of the problem.
* Once the root cause is identified, implement corrective actions to prevent the problem from recurring.


== Example of an organization's server unexpectedly shuts down ==

'''Problem''': The server shut down unexpectedly.

* '''Why?''' The server overheated.
* '''Why did the server overheat?''' The cooling system failed.
* '''Why did the cooling system fail?''' The air filters were clogged with dust.
* '''Why were the air filters clogged with dust?''' They hadn't been cleaned or replaced in over a year.
* '''Why hadn't they been cleaned or replaced?''' There was no scheduled maintenance or reminder system in place.

'''Root Cause''': The absence of a scheduled maintenance or reminder system for server upkeep led to the server's unexpected shutdown. '''Corrective Action''': Implement a scheduled maintenance plan and set reminders for regular checks and replacements of crucial components.


== Example of low response time on a company's e-commerce website ==

'''Problem''': The e-commerce website is responding slowly.

* '''Why?''' The server is experiencing high CPU usage.
* '''Why is the server experiencing high CPU usage?''' There's a spike in traffic.
* '''Why is there a spike in traffic?''' A promotional campaign was launched today.
* '''Why was the server not prepared for this spike given the promotional campaign?''' The marketing team didn't notify the IT department about the expected increase in traffic.
* '''Why didn't the marketing team notify the IT department?''' There's no established communication protocol for such events.

'''Root Cause''': Lack of communication protocol between the marketing and IT departments led to the server not being prepared for a spike in traffic. '''Corrective Action''': Establish a communication protocol between departments for events or campaigns that can lead to significant changes in website traffic.

By following the 5 Whys methodology in these examples, the organizations were able to pinpoint the underlying issues and take corrective action to prevent future problems.


= Guideline document =

* '''Department''': [Department Name]
* '''Date''': [Date]
* '''Facilitator''': [Facilitator's Name]
* '''Team Members''': [Names of those involved in the analysis]


== 1. Problem statement ==

Clearly define and describe the problem.

[Description of the observed problem]


== 2. The 5 whys ==

Start with the problem statement, and then proceed to ask "Why?" until the root cause is identified.


=== Why 1 ===

'''Question''': Why did [problem or outcome from the previous answer] happen?

'''Answer''': [Answer to the first "Why?"]


=== Why 2 ===

'''Question''': Why did [outcome from the previous answer] happen?

'''Answer''': [Answer to the second "Why?"]

(Continue the process as needed...)


== 3. Root cause identification ==

[Identified root cause after asking the series of "Why?" questions]


== 4. Corrective actions ==

* '''Proposed Action''': [Suggested action to address the root cause]
* '''Responsible Person/Team''': [Name/Team assigned to execute the action]
* '''Deadline''': [Date by which the action should be implemented]


== 5. follow-up ==

* '''Review Date''': [Date when the team will review if corrective actions have been effective]
* '''Status''': [Pending/Completed/Effective/Ineffective]
* '''Notes''': [Any observations or further recommendations]


[[Category:documentation templates]]

5 whys

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Category:Documentation templates

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[[Category:Templates]]
Automatically created category

Documentation templates

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Brainstorming Whiteboard

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[[Category:confluence templates]]

Brainstorming Whiteboard

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Category:Confluence templates

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Maintenance script: Auto-created category confluence templates

[[Category:Templates]]
Automatically created category

Confluence templates

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Quarter OKR roadmap

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Template for defining the Objectives and Key Results of this quarter


= Year - Quarter number (2025 - Q1) =

{| class="wikitable" table-width="1552" layout="center" ac:local-id="e6df3cf3-5ddc-438e-9904-c545644259ec"
|-
! '''Objetive'''

! '''Key Result'''

! '''priority'''

! '''effort'''

! '''value'''

! '''status'''

! '''documentation'''

|-
|
|
|
|
|
|
|
|-
| What do we want to achieve

| What is the expected measurable outcome

| {{Status
|title = LOW
|colour = Red
}}
{{Status
|title = medium
|colour = Green
}}
{{Status
|title = High
|colour = Blue
}}

| {{Status
|title = low
|colour = Blue
}}
{{Status
|title = medium
|colour = Green
}}
{{Status
|title = HIGH
|colour = Red
}}

| {{Status
|title = LOW
|colour = Red
}}
{{Status
|title = MEDIUM
|colour = Green
}}
{{Status
|title = high
|colour = Blue
}}

| {{Status
|title = Definition
}}
{{Status
|title = in development
|colour = Green
}}
{{Status
|title = blocked
|colour = Red
}}
{{Status
|title = Completed
|colour = Blue
}}

| Confluence Link

|}

Cybersecurity

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https://hack4u.io/cursos/hacking-web/


[[Category:IT Resources]]

Cybersecurity

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https://hack4u.io/cursos/hacking-web/

Site analyzers

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https://web-check.xyz/


[[Category:IT Resources]]

Site analyzers

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https://web-check.xyz/

Performance

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unlighthouse


[[Category:IT Resources]]

Performance

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unlighthouse

Pen testing

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https://www.wireshark.org/


[[Category:IT Resources]]

Pen testing

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https://www.wireshark.org/

IT Reading Doc

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= Articles =

https://samirs-organization-6.gitbook.io/github-actions-by-example


= Books =

* Psychology of Computer Programming - Gerard
* Mythical Man-month - Frederic
* Accelerate Devops - Nicole
* Site Reliability Engineer


[[Category:IT Resources]]

IT Reading Doc

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Documentation tools

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* [https://obsidian.md/ Obsidian]
* [https://www.atlassian.com/es/software/confluence Confluence]
* [https://www.notion.com/ Notion]
* [https://www.mediawiki.org/wiki/MediaWiki MediaWiki]


[[Category:IT Resources]]

Documentation tools

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Code assistants

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[https://marketplace.visualstudio.com/items?itemName=CodeViz.codeviz VS codeViz]

CodeViz is '''a VS Code extension that generates interactive diagrams of codebases, from system architecture down to function call graphs'''

[https://codeassist.google/ Gemini Code Assist]

Google AI assistant for VS and Jetbrains


[[Category:IT Resources]]

Code assistants

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Books sources

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https://en.wikipedia.org/wiki/Library_Genesis

https://en.wikipedia.org/wiki/Z-Library


[[Category:IT Resources]]

Books sources

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https://en.wikipedia.org/wiki/Library_Genesis

https://en.wikipedia.org/wiki/Z-Library

Code with local AI, linux & VSCode

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<ul>
<li>install ollama: https://www.ollama.com/download/linux</li>
<li>how to download a model from https://www.ollama.com/search
<ul>
<li>choose gpt-oss, deepseek-r1, gemma or qwen3-coder</li>
<li>type in the terminal “ollama pull gpt-oss:20b”</li></ul>
</li>
<li>install “continue” extension in VSCode https://docs.continue.dev/getting-started/install</li>
<li>drag the “continue” extenstion icon from the left to the right side</li>
<li>configure the extension:
<ul>
<li>there is no need to login</li>
<li>in the “select model” under the chat, select “Ollama” and the installed model</li>
<li>if you ask anything, it will throw an error that the model can’t be found</li>
<li>In the config.yaml that should have been opened (/home/$user/.continue/config.yaml) modify “models” section for this:
<syntaxhighlight>models:
- name: gpt-oss:20b
provider: ollama
model: gpt-oss:20b
roles:
- chat
- edit
- apply
- autocomplete</syntaxhighlight>
This is because there is some kind of bug (right now) and it appends “openai” in the model name, it doesn’t use the proper name we pulled before from ollama repository.</li></ul>
</li>
<li>add another models depending on your hardware capabilities:
<ul>
<li>RTX 3090
<ul>
<li>gpt-oss:20b</li>
<li>deepseek-r1:14b</li>
<li>qwen3-coder:30b</li>
<li>llama3.1:8b</li></ul>
</li></ul>
</li></ul>


[[Category:AI Resources]]

Code with local AI, linux & VSCode

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Generic AI resources

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= Text General purpose =

* [https://chatgpt.com/ chatGPT]
* [https://aistudio.google.com/prompts/new_chat Gemini]
* [https://claude.ai/ Claude]
* [https://grok.com/ Grok]
* [https://chat.deepseek.com/ Deepseek]
* [https://www.perplexity.ai/ Perplexity]


= Text to image =

* [https://openai.com/es-ES/index/dall-e-3/ Dall-e]
* Flux
** [https://playground.bfl.ai/image/generate playground]
** [[UserDocumentation:Knowledge_Central/Resources/IT_Resources/AI_Resources/AI:_Text_to_image_in_local|local]]


= Video =

* [https://veo3.ai Veo3]
* [https://openai.com/sora/ Sora]
* [https://runwayml.com/ Runway]
* [https://app.pixverse.ai/ Pikalabs]


= Music =

[https://suno.com Suno]


= Voices =

[https://elevenlabs.io Eleven labs]


= Media =

[https://aistudio.google.com/gen-media Google AI Studio]

[https://fal.ai/ FAL]


= Documentation expert =

https://notebooklm.google.com


= Slides presentation =

[https://www.kimi.com/kimiplus/cvvm7bkheutnihqi2100 Kimi Slides]


= Local AI =

https://pinokio.co/

[https://lmstudio.ai/ LM Studio]


[[Category:AI Resources]]

Generic AI resources

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AI: Text to image in local

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In this case, where are going to use Flux (https://bfl.ai/)

Flux (styled often as '''FLUX''' or '''FLUX.1''') is a family of '''text-to-image generation models''' developed by ''Black Forest Labs (BFL)''.

Key features & properties:

{| class="wikitable" table-width="760" layout="default" ac:local-id="c24da384-3fc5-4ebc-ad49-82129ee44632"
|-
! Feature

! Description

|-
| '''Architecture'''

| A “rectified flow transformer” model, ~12B parameters, combining approaches from diffusion, transformer flow matching, etc.

|-
| '''Model Variants / Licencing'''

| There are several variants:

|-
| – '''FLUX.1 [schnell]'''

| The fast, distilled version. Open source, Apache-2.0 • high speed, fewer inference steps.

|-
| – '''FLUX.1 [dev]'''

| More powerful, more resource-intensive, open weights under non-commercial licence. Better fidelity.

|-
| – '''FLUX.1 [pro]'''

| Commercial / API access only. Higher quality, possibly features not in open models.

|-
| '''Additional modes'''

| E.g. “Ultra”, “Raw” for very high resolution or photorealism. Also “Kontext” for editing / in-context image generation.

|-
| '''Usage'''

| Can be used via APIs, via HuggingFace / other model hubs, or locally with GUIs / “WebUIs” (Stable Diffusion‐style UIs like Forge, ComfyUI), etc.

|}

So it’s kind of a next‐gen Stable Diffusion-like set of models, with some distilled/faster versions and some high-quality ones. Good prompt following, potentially strong image quality.

-----


=== Use cases / What it is used for ===

* Generating images from text prompts (text→image).
* Image editing / in-context generation: e.g. “Kontext” mode which allows combining text + image input to guide edits.
* In creative workflows, concept art, renders, style transfer, etc.
* Can be used as a base for fine-tuning (LoRA, etc.), or with low-bit quantization etc. to run on lower-VRAM hardware.


= How to install & run Flux locally (CLI + GUI) =


== Graphical User Interface ==

To do it, we need another software to manage the GUI, in this case we will use comfyUI. It works with a node-based workflow.


=== Installation ===

<ul>
<li>Follow the guide for your OS: https://comfyui-wiki.com/en/install/install-comfyui
<syntaxhighlight># For Ubuntu:
sudo apt install python3 python3-pip python3-venv
python3 -m venv comfy-env
source comfy-env/bin/activate

pip install comfy-cli
comfy --install-completion

comfy install

comfy --workspace=/path/to/your/workspace install
#comfy --here install

#GPU support for Nvidia
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
#CPU support only
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu</syntaxhighlight></li>
<li>Download Flux.1 dev here https://huggingface.co/black-forest-labs/FLUX.1-dev/tree/main. You need to signup and download file into local folder ~/comfyUI/models/difussion_models/. This will be the base model to use.</li>
<li>Download VAE (used to learn and generate new data based on patterns and features from a given dataset) http://huggingface.co/stabilityai/sd-vae-ft-mse-original/blob/main/vae-ft-mse-840000-ema-pruned.safetensors and place it in models/vae</li>
<li>Download CLIP Loader https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors and place it in models/text_encoders folder</li>
<li>Download T5 https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors and place it in models/text_encoders folder</li>
<li>If you want to use a custom Model (checkpoint) or LoRA, you can download them from civitai.com</li></ul>


=== Launch comfyUI ===

<syntaxhighlight>comfy launch</syntaxhighlight>

=== Load Template ===

In the left side, there are multiple you can use.


=== Configure workflow ===

* for adding new nodes, double click on an empty space


[[Category:AI Resources]]

AI: Text to image in local

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Category:AI Resources

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Category:IT Resources

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Design tools

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in a browser, execute:

<syntaxhighlight>document.designMode = "on";</syntaxhighlight>
to enable live edition


[[Category:Design resources]]

Design tools

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in a browser, execute:

<syntaxhighlight>document.designMode = "on";</syntaxhighlight>
to enable live edition

Category:Design resources

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[[Category:Knowledge Central]]
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Category:Resources

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Project evolution phases

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We must know in which state is the company before start taking decisions following the 3X model. This model doesn't only apply to only the company, but also for each for their projects / business units.

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_project_evolution_phasesimage-20250419-082049.png|600px|center]]


== Explore ==

There is an idea for solving a problem / necessity on the market. The uncertainty of knowing if the idea will solve the problem is so high that we will have to explore quickly and provide rapid solutions to materialize the solution. "Don't worry, be crappy". Use NoCode, SaaS or whatever to test it fast.


== Expand ==

We have proven that our solution solves the problem / necessity. We are starting to make marketing of it and implementing new features of the product. Now we have to focus on the expansion. The decisions that are taken must not suppose a bottleneck for the company. We can't over promise to be kind, we have to explain properly and sincerely what can be done or not. Ask why some goals are set.


== Extract ==

Service works properly and business is predictable. We have to apply dynamics and techniques to maximize company profit reducing costs.

-----


= How to =

Evolution doesn't have to be iterative, but incremental

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_project_evolution_phasesimage-20250419-082208.png|760px|center]]

Example of a Minimum Viable Project:

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_project_evolution_phasesimage-20250419-082244.png|740px|center]]

-----


= Consolidate standards =

Consolidating standards in a project context means capturing, harmonizing, and embedding all agreed‑upon processes, tools, metrics, and best practices into a single, accessible framework. Rather than letting teams reinvent the wheel, you create a “source of truth” that everyone refers to—covering everything from coding conventions or documentation templates to approval workflows and quality criteria.

Continuous improvement relies on iterative cycles of planning, executing, checking, and acting. Without a stable set of baseline standards, each improvement cycle risks drifting away from prior gains or introducing inconsistency. By consolidating standards you:

* '''Lock In What Works''': Capture lessons learned, process tweaks, and newly discovered best practices so that proven methods become part of the standard toolkit.
* '''Ensure Repeatability''': When everyone follows the same documented approach, successes are reproducible across teams and projects.
* '''Measure Progress Accurately''': With clear metrics and definitions in place, you can objectively compare “before” and “after” states and quantify improvement.

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_project_evolution_phasesimage-20250419-082832.png|760px|center]]


= Design cycle =

A '''design cycle''' is a structured, iterative process that guides teams from understanding a problem all the way through to delivering—and then improving—a solution. Rather than trying to “get it right” on the first pass, a design cycle breaks work into repeatable stages, each with its own goals and checks, so you continually learn, adapt, and reduce risk.

* '''Agility & Adaptability:''' Each pass through the cycle refines both the product and the process, making the team better at estimating, planning, and executing.
* '''Reduced Waste:''' Early validation and frequent testing ensure you spend less time on non‑viable features or solutions.
* '''Higher Quality & User Satisfaction:''' Continuous user input and rigorous testing lead to products that truly meet needs and perform reliably in the field.
* '''Transparent Progress:''' Clear, repeatable stages with built‑in checkpoints help stakeholders see exactly where you are—and what remains—at any time.
* '''Scalable Governance:''' Whether you’re a small startup or a large enterprise, this framework can flex to projects of any size while maintaining consistency in how work gets done.


== Steps of a design cycle ==


=== 1. Idea ===

* '''Encourages Creativity & Divergent Thinking:''' By explicitly carving out time to brainstorm freely, teams generate a wider range of possible solutions, some of which may be truly innovative rather than incremental.
* '''Early Engagement:''' Stakeholders (users, sponsors, cross‑functional experts) can weigh in from the very beginning, ensuring diverse perspectives shape the direction.


=== 2. Validate ===

* '''Risk Reduction:''' Quickly screens out unworkable or unprofitable ideas before dedicating development resources.
* '''User‑Centered Focus:''' Using lightweight techniques (surveys, interviews, paper prototypes) ensures that only ideas with real user appeal advance.


=== 3. Define Solution ===

* '''Clarity of Scope:''' Translates validated ideas into concrete requirements, wireframes, or specifications—removing ambiguity about what you’re building.
* '''Alignment:''' Gets all stakeholders on the same page around objectives, success metrics, and “must‑have” vs. “nice‑to‑have” features.


=== 4. Develop ===

* '''Incremental Progress:''' Breaking the build into smaller, manageable increments makes scheduling, resource planning, and progress tracking more reliable.
* '''Early Value Delivery:''' Even partial prototypes or alpha releases can start generating feedback or revenue sooner.


=== 5. Test ===

* '''Quality Assurance:''' Systematic functional and usability testing uncovers defects and UX issues before launch, reducing costly post‑release fixes.
* '''Data‑Driven Refinement:''' Insights from real users and automated tests guide targeted improvements rather than guessing at what needs work.


=== 6. Deliver ===

* '''Predictable Release Cadence:''' By treating “delivery” as a distinct phase, teams can lock down deployments, prepare support/training materials, and manage change more smoothly.
* '''Market Responsiveness:''' A clear delivery milestone lets marketing, sales, and operations plan around a firm go‑live date.


=== 7. Feedback ===

* '''Continuous Improvement Loop:''' Capturing user reactions, usage metrics, and internal retrospectives feeds directly into the next Idea phase—so the cycle never goes stale.
* '''Stakeholder Confidence:''' Demonstrates that you listen and adapt, which builds trust and often uncovers new revenue or efficiency opportunities.


[[Category:manage objectives]]

Project evolution phases

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Story mapping

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When tackleling an objective it is necessary to make a good previous study

* Have the objective clear
* Define strategies to accomplish the objective
* Make tactical materialization proposals

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_Story_mappingimage-20250419-080709.png|760px|center]]

We must have a "model" for our application, in order to know which type of client are we dealing with and their main characteristics.

It is recommendable that proposal meets INVEST:

* Independent: they can be implemented in any order
* Negotiable: details can be discussed between all parts
* Valuable: must provide value to the user
* Estimable: it doesn't have an excessive complexity
* Small: can be materialized in a short time
* Testable: we can make tests to verify it works properly

All objectives must be measurable through KPIs.


== Establish priorities ==

We must value the priority of the strategical and tactical proposals through ICE:

* Impact: how much is it going to affect in the evolution of our project
* Confidence: how confident do we have that it will be successful
* Ease: complexity of their development

Each of them has a value of 0 to 10. Priority is obtained from the sumatory of them all. With this, we can establish a Minimum Viable Increment. The higher the value, the more a quick win it will be.


== Three friends ==

It is referred to the 3 primary perspectives to examine before, during and after the development phase of an increment iteration.

* Business: which new value I want to provide?
* Development: How to build a solution for this requirement?
* QA: given that new value, how can I test it? given that solution, what could happen?

We share an understanding of the requirement and we identify possible confusions and disagreements.


[[Category:manage objectives]]

Story mapping

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Scale a business

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Scaling a business is not just about increasing sales or expanding the market footprint; it involves a holistic approach that ensures that as the business grows, it remains sustainable, profitable, and aligned with its core values and objectives. This process requires a depth of understanding in several areas of business. Scaling is not just about growing bigger; it's about growing smarter. By understanding it, business leaders can ensure that their scaling efforts are sustainable, profitable, and in line with their long-term vision.


= Iron triangle =

Given a determinated solution to a problem, it has a scope, it takes time to complete it and has associated costs. This triple restriction must be taken into account when ensuring our product quality, due to we need to have a balance between them. Agile methodologies guide us to make these development triangles smaller.

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_Scale_a_businessimage-20250419-093313.png|536px|center]]


= Understanding the market =

It's paramount for businesses to deeply understand their target audience and market trends. This involves knowing the consumer's preferences, needs, pain points, and purchasing behaviors. Equally crucial is understanding the competitive landscape: who the key players are, their strengths and weaknesses, and potential opportunities for differentiation.


= Financial acumen =

Financial management is at the heart of scaling. This entails not just managing current finances but also forecasting future financial needs, understanding cash flow, and securing the necessary capital for expansion. Knowing when and how to reinvest profits or when to seek external funding is crucial.


= Operational efficiency =

As businesses grow, their operations can become more complex. This can lead to inefficiencies, which can erode profits. It's important to continuously refine and optimize operational processes, making use of modern technologies, software solutions, and best practices.


= Human resources and leadership =

A growing business often means a growing team. Understanding how to recruit, train, and retain talent is vital. Additionally, leadership skills are needed to inspire and guide the team, ensuring everyone is aligned with the company's mission and objectives.


= Product or service innovation =

To stay ahead of the competition and cater to an expanding clientele, continuous innovation is essential. This could mean refining existing products or services, introducing new ones, or even pivoting the business model based on emerging market needs.


= Customer relationship management =

Maintaining strong relationships with existing customers while attracting new ones is a balancing act. Implementing effective customer service strategies and utilizing tools like CRM software can help manage and analyze customer interactions, ensuring satisfaction and loyalty.


= Technology and digital transformation =

In today's age, leveraging technology is no longer optional. Whether it's e-commerce platforms, data analytics, or cloud solutions, technology plays a pivotal role in scaling. A business needs to understand which technologies are most relevant to their operation and how to integrate them effectively.


= Risk management =

With growth comes new challenges and potential threats. These could range from operational risks, financial vulnerabilities, to external factors like market fluctuations or geopolitical changes. Being prepared with a risk management strategy is essential.


= Regulatory compliance =

Especially for businesses expanding into new regions or countries, understanding and complying with local regulations, taxes, and laws is crucial to avoid legal complications and maintain a positive brand reputation.


= Cultural and organizational adaptability =

As the business scales, the organizational culture might need to evolve. This could involve restructuring teams, adapting to new market cultures, or integrating new corporate values. Being adaptable is key to navigating these shifts successfully.


= Business types =

* '''viable''': are those where income and costs grow equally. For example a restaurant: if you want to allow more clients, you need more waiters.
* '''scalable''': it is a model where reached a certain point incomes grow more than the growth of the costs. Sales increment tends to be exponential, while costs increments linearly. This type of projects is risky, base projects that are expected to be highly profitable have a high failure risk.


= Bottlenecks =

To avoid limitations during project evolution, it is necessary the identification of those processes that limit the proper consecution of objectives for the lack of resources.

You need to be ready to adapt your strategy and make the necessary changes when you find out that something about the current situation is wrong. As in many other situations, it becomes clear that we need to take an agile stance. As software developers we need to be ready for change, caused by new insights of stakeholders, or the experience of a bottleneck in the current process. Continuously look for clues that indicate bottlenecks, teams frequently blocked by others, etc.

The one rule that matters is maximizing our ability to frequently deliver value to customers.

[[File:UserDocumentation_Knowledge_Central_KC_Project_Project_management_manage_objectives_Scale_a_businessimage-20250419-093403.png|760px|center]]


[[Category:manage objectives]]

Scale a business

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