Signal over noise. Founder-led takes on execution intelligence, the death of process theater, and building what CTOs actually need.
We built 12 free engineering intelligence tools. No sign-up, no credit card, no gates. Paste a GitHub org URL and get real data about your engineering organization in seconds.
Paste a GitHub org URL. Get a health score, key risks, velocity trends, and strategic recommendations. This is what your CTO should be presenting to the board.
We tracked Vercel's commit velocity over 13 weeks. STABLE at 12.1 commits/week — but the pattern tells a deeper story. Surge weeks, trough weeks, and what it means.
We scanned Vercel's GitHub org and found a MODERATE AI signal — 22-31% estimated AI-assisted code. Our free scanner gives you the real number in 60 seconds.
We benchmarked Vercel against DORA performance categories. They scored ELITE — 0.0 day median cycle time, 90.9% merge rate. Where does your team land?
Your CFO tracks cost per customer, cost per lead, cost per acquisition. Nobody tracks cost per commit. We scanned Vercel — $1,910 per commit. The number is eye-opening.
Supabase has a bus factor of 10 — their top 2 contributors own 16% of all commits. Bus factor isn't theoretical. It's a number you can calculate right now.
We audited Vercel's GitHub org and found naming duplicate clusters and repos that should be archived. Every unmaintained repo is a security risk. Here's how to clean up.
For 15 years, engineering organizations assumed humans are the source of truth. That assumption shaped Jira, sprint planning, and velocity charts. AI changes everything.
Most companies can't tell you what last month's engineering spend actually produced. InteliG connects every commit to cost and strategy — so you see exactly where money creates value and where it burns.
I asked InteliG's AI reasoning engine one question about my engineering org. It scored every commit, compared them, identified patterns, and gave me a recommendation. Here's what happened.
DX measures developer experience through surveys and sentiment. InteliG measures engineering reality through code, strategy, finance, and AI reasoning.
Faros AI aggregates engineering data into dashboards. InteliG connects code to strategy, finance, and decisions — then reasons about it with AI.
Hatica gives engineering managers visibility into team workflows. InteliG gives CTOs intelligence across code, strategy, finance, and decisions — powered by AI reasoning.
Jellyfish sells dashboards to executives. InteliG gives CTOs a reasoning engine that connects code, strategy, finance, and decisions — without a six-figure contract.
Keypup tracks DORA metrics and developer analytics. InteliG connects code to strategy, finance, and decisions with an AI reasoning engine that answers questions no dashboard can.
LinearB measures developer activity. InteliG connects code to strategy, cost, and decisions. Here's why metrics alone leave CTOs guessing.
Pluralsight Flow (formerly GitPrime) tracks developer activity patterns. InteliG connects that activity to strategy, cost, and business outcomes.
Sleuth tracks DORA metrics and deployment frequency. InteliG connects deployments to strategy, cost, and business outcomes with AI reasoning.
Swarmia tracks developer productivity signals. InteliG connects code to strategy, finance, and decisions with an AI reasoning engine that answers any question about your org.
Waydev tracks developer work patterns and DORA metrics. InteliG connects engineering output to strategy, finance, and decisions — with an AI reasoning engine that actually reasons.
Tests don't find bugs — they assert assumptions you already have. AI agents that reason over your code's control flow and failure states catch bugs your test suite never will.
Design-to-code tools solve the cheapest part of software. The AI IDE collapses PM, designer, engineer, and architect into one loop. Any tool wrapping a frontier model and exposing 10% of its capability is fighting a losing battle.
Most PMs were already struggling before AI showed up. Only five archetypes survive: outcome-obsessed, technically fluent, signal-driven, decision-makers, and AI-augmented. Everyone else is pure latency.
Engineering Managers existed to translate strategy into tickets and report status upward. AI now does all of that faster, cheaper, and continuously. The role survives only for those who design execution systems.
When a team's response to a technical bottleneck is 'add more fields to the ticket,' they're operating with pre-AI mental models. AI doesn't need more fields. It needs context.
Sales has dashboards. Marketing lives in funnels. Finance tracks every dollar. Engineering runs on vibes and Jira tickets. It's time CTOs looked at their own data.
Feature-Driven and DDD aren't competing approaches. I built InteliG with DDD + CQRS + Event Sourcing across 17 bounded contexts. Here's what actually works.
SaaS won't die. Mediocre SaaS will. Here are the 6 types of SaaS companies that survive the AI era — and why everything else is a feature waiting to be absorbed.
Strategy that lives in slides and Notion is invisible to developers and AI tools doing the actual work. The Signal Method puts strategy, decisions, and knowledge directly in the repo so AI can reason over it.
Repos don't lie. Dashboards do. If you want the truth about who's contributing, what it costs, and what's shipping — read the repo. Everything else is a story someone typed.
AI won't replace people. People who use AI to collapse time, cost, and complexity will replace everyone else. Here are the 7 types that survive.
Sales has quotas, rankings, and dashboards. Engineering has Jira tickets and vibes. It's time to know who your top developers actually are — with data, not opinions.
Jira tracks what someone typed, not what actually happened. Story points are astrology, sprint velocity is a vanity metric, and the entire premise of ticket-first engineering is broken.
Every great abstraction follows the same pattern: do it manually, recognize the pattern, encode it, let the system take over. I'm applying that to the CTO role itself.
Big companies love saying 'we operate like a startup.' They don't. They confuse activity with progress, tools with truth, and motion with speed. Visibility is the real differentiator.
Corporate marketing is written by committees, optimized for safety, and read by no one. In the AI era, boring is invisible. Say something real or don't post at all.
No executive has ever woken up thinking about how many tickets moved to Done. They care about two things: how much did we spend on initiative X, and where are we at. Tickets can't answer either question.
InteliG wasn't designed for 'users.' It was designed for me. Why the best SaaS companies are born from founder pain, not market research.
Not everyone benefits equally from AI. Here's a brutally honest tier ranking of who wins, who survives, and who gets replaced in the AI era.
The AI era didn't invent a new way to build software. It removed the excuses. Why small teams shipping fast was always the right model.
Google Docs. Confluence. Notion. Internal wikis. They're all graveyards nobody reads. The future of documentation lives in the repo — where your AI agents are.
An open-source methodology for SaaS companies that connects every decision, meeting, and line of code into a single traceable system. Fork it. Clone it. Build better products.
Labels are manual, inconsistent, and useless at scale. InteliG Commit Intelligence analyzes every commit and classifies automatically — bugs, features, refactors, docs — no tickets or labels required.
Every CTO asks 'what are my developers working on?' and never gets a real answer. Cognis is InteliG's reasoning engine — ask anything, get evidence-backed answers.
The entire category of dev analytics is stuck in the dashboard paradigm. CTOs don't need more charts — they need a system that thinks. It's time for actual intelligence.