Daniel Arevalo

Product Architect and Design Engineer interested in Cybersecurity 🔑, Blockchain 🔗, Machine Learning 🤖 and Human-Computer Interaction 🧮.

[Daniel Arevalo @danielfae]

There isn’t one single skill that allows PMs to become irreplaceable. AI creates a direct line of coordination and delegation between customer/user facing roles and builders. PMs will have to go back to the roles they came from in the design, business or development fields.

[Daniel Arevalo @danielfae]

In an industrial demo, IT asks if data leaves the perimeter. OT asks if it triggers alarms on live machinery.

Security slides convince neither.

Running a local open-weight model on-prem with visible step checks answers both.

[Daniel Arevalo @danielfae]

Finding vulnerabilities with AI in industrial OT is becoming cheap. Fixing them safely is the real barrier.

You cannot auto-patch a legacy PLC or reboot a power substation without risking downtime. The bottleneck is having the operational context to remediate safely.

[Daniel Arevalo @danielfae]

Designers stayed attached to early versions because building alternatives cost too much time.

When agents reduce implementation cost to zero, that sunk cost disappears. You can direct systems to explore multiple competing directions and discard what fails without hesitation.

[Daniel Arevalo @danielfae]

Prompting a single model to write full features breaks down fast.

I run specialized agents instead: PRD planning from raw ideas, automated refactoring before merge, and browser QA for visual regressions.

The real build is the orchestration pipeline underneath.

[Daniel Arevalo @danielfae]

Generating code became cheap overnight, but it raised the bar for understanding software.

When an agent handles syntax, the bottleneck shifts to evaluating architectural tradeoffs, reviewing diffs with intent, and keeping the mental model of the system intact.

[Daniel Arevalo @danielfae]

Trusting an AI agent with implementation details works, but letting it define boundaries is how codebases rot.

Micromanaging boilerplate defeats the purpose. The actual job is verifying domain rules, system architecture, and why a change exists.

[Daniel Arevalo @danielfae]

The designer-engineer handoff collapses the moment you orchestrate agents yourself.

Once a product designer understands data structures and execution loops, moving from intent to working software is direct. You own the product from architecture down to production.

[Daniel Arevalo @danielfae]

Context architecture is what actually makes coding agents reliable.

I run a 3-layer system:
1. Global conventions across all projects
2. Project architecture and stack boundaries
3. On-demand reference files loaded only when a task needs them.

[Jesper Bylund -- just/acc @JesperBylund]

This is the future. Software without gatekeepers means a lot higher floor for software quality

[Daniel Arevalo @danielfae]

Calling modern AI development "vibe coding" completely undersells the work.

Writing syntax was the easy part. The real discipline is context management, tight system boundaries, and product taste in directing intent.

[Daniel Arevalo @danielfae]

The bottleneck for adoption of complex industrial or enterprise platforms is almost never adding more capability. It is instead the capacity of a company to focus on closing the cognitive gap to use existing features and let users gain any progress or even complete their tasks.

[Daniel Arevalo @danielfae]

@BarnehamaArye @foundrymgt Definetely! Can relate, it is a huge problem that makes companies optimize for sales when they are lacking a lot in product!

[Daniel Arevalo @danielfae]

Waking up like…Which wonders would today bring to the world of Cybersecurity 😅

[Daniel Arevalo @danielfae]

Building my Obsidian agent pipeline taught me more about directing agents in a month than a year of reading ever could.

It runs BYOM with Anthropic, OpenAI, or local models. A few people I trust are running daily workflows through it now. DM if you want to try it.

[Daniel Arevalo @danielfae]

I built an Executive Virtual Assistant on top of my Obsidian pipeline.

Its mission control deck surfaces operational blind spots: untriaged inputs, projects that went quiet without a resolution, and shipped work that never converted into documented learning.

[Daniel Arevalo @danielfae]

I used to keep hundreds of notes in Obsidian topic folders that I barely checked.

Pointing an agent at a static folder fails because it lacks context. Giving it a structured pipeline with explicit state transitions makes steering it straightforward.

[Anthropic @AnthropicAI]

We've signed an agreement with Google and Broadcom for multiple gigawatts of next-generation TPU capacity, coming online starting in 2027, to train and serve frontier Claude models.

[Daniel Arevalo @danielfae]

I have been using it since the feature came out! a great way to iterate on the frontend while letting Claude Code keep working on other tasks.

[Lee Robinson @leerob]

Cursor tip: if you're doing web dev, there's an integrated browser!

The agent can read console logs, network requests, and even control the browser to do automated testing for you.

You don't have to install any third-party MCP servers, just works 😄

[Lee Robinson @leerob]

Cursor tip: if you're doing web dev, there's an integrated browser!

The agent can read console logs, network requests, and even control the browser to do automated testing for you.

You don't have to install any third-party MCP servers, just works 😄

[Karri Saarinen @karrisaarinen]

https://t.co/RU33K24RsJ