One-time purchase. Build your AI infrastructure.
Ship Product Code Faster.
With an AI Brain Built for Devs.
For developers doing serious product work with Claude — prototyping, backend, frontend, tests, web/mobile/desktop/browser extensions. An autonomous yalla pipeline, agent teams for complex features, language-specific reviewers, and production-tested hooks. Ships with MemoryOS SQL backbone from day one.
100+ commits/day ready • Agent teams enabled • 48-hour async support
What If Your AI
Shipped Features For You?
Same Claude Code. Same prompt. The only difference: a brain tuned for product development.
"Add user profile page with avatar upload"
"I'll help you add a user profile page. Let me start by asking about your tech stack, existing auth setup, and preferred image hosting. Can you share your current database schema?"
"Add user profile page with avatar upload"
"Running /yalla... Plan: 4 phases (schema, upload endpoint, UI, tests). Read your CLAUDE.md — stack is Next.js + Supabase + shadcn. Analyzed existing auth middleware. Wrote migration, /api/avatar-upload with 5MB limit and Vercel waitUntil, ProfilePage.tsx using shadcn Form + Avatar. Tests: 6 Playwright specs pass. Review: 0 blockers. PR #442 opened."Plan, build, test, review, ship — one command.
"Review my recent changes"
"I'd be happy to review your code. Please paste the diff or specify the files you'd like me to look at."
"Review my recent changes"
"Running /yalla-review on branch session/task-442. 3 reviewers ran in parallel: kieran-typescript (PASS), security-sentinel (FAIL: file upload missing MIME whitelist), performance-oracle (PASS). Fix: add allowlist [image/jpeg, image/png, image/webp] in line 23 of api/avatar-upload.ts. Blocker — cannot ship until fixed."Adversarial review catches what you miss.
"How did we handle rate limiting in the other project?"
"I don't have visibility into your other repositories. Could you share the relevant code?"
"How did we handle rate limiting in the other project?"
"Searched your indexed repos. In acme-api (committed last month), you used Upstash Redis with sliding window — 100 req/min per IP, custom KV key pattern. In consulting-app, token bucket via next-rate-limit. Acme-api approach is more aligned with your current Vercel stack. Here's the middleware pattern ready to adapt."Your brain searches across every repo you've indexed.
What Is a Second Brain?
Every Claude session starts from zero — unless you engineer the context it receives. A Second Brain is the system that ships with your stack, your review rules, and your codebase already indexed.
Persistent Context
Your stack, review strictness, architecture decisions, and indexed codebases — stored in a local SQL database so Claude knows them before every session.
Agent Teams
Planner + implementer + tester + 3 reviewers running in parallel. Adversarial review catches what a solo run misses.
Yalla Pipeline
/yalla runs plan → build → test → review → ship in one command. /yalla-team adds adversarial multi-agent review for complex features.
Session Hooks
branch-guard blocks edits on main. Session lifecycle auto-tracks every commit to the active task. Production-tested hooks, zero config.
Plus: Dev Infrastructure
Indexed Codebases
Any repos you point at get cloned + semantically indexed. /recall searches across all of them from day one.
Language Reviewers
kieran-typescript, kieran-python, vercel:react-best-practices, security-sentinel. Tuned to your primary stack.
Pre-Deploy Gates
/validate-build runs TS, lint, and tests before you ship. Blocks regressions at the door.
MemoryOS SQL Backbone
Every decision, every pattern, every test failure persisted with decay scoring. The brain compounds as you ship.
How it fits together
You
talk to Claude
Second Brain
structures your context
Claude
works with full context
Pipeline
plan → build → test → review → ship
Better Output
every time
The result: Instead of re-explaining your stack every session, Claude already knows. It has context from your last feature, your review strictness, your test framework — across every session. Plus an autonomous pipeline that ships PRs while you focus on architecture.
Static Context vs Engineered Context
Static Context
Engineered Context
Setup
You copy-paste a system prompt
AI learns your stack from a questionnaire + pastes your CLAUDE.md
Memory
Remembers what you wrote down — forgets what it learned
Captures patterns automatically, detects decay, compounds over months
Tools
Copy diffs in and out of AI
AI reads your repo, PRs, CI status, and indexed codebases directly
Quality
Hope the code is good
Language-specific reviewers score every PR + block on Fail
Maintenance
Breaks when framework updates
Vercel/shadcn/Turbopack skills auto-update; hooks stay deterministic
Ownership
Locked in vendor platform
Your database, your hooks, your rules — all in code you control
This is why ChatGPT Memory, Notion AI, Cowork, and DIY setups all hit the same wall.
Personalized
not templated
Connected
not isolated
Measured
not guessed
Compounding
not static
Owned
not rented
Built for How Devs Actually Ship
Five patterns we see in every product-dev setup. Which one is you?
The 100-commits-a-day Shipper
You push code constantly with Claude. Small PRs, fast iteration. The bottleneck isn't writing code — it's keeping the brain from forgetting yesterday's decisions.
"I ship more in a week than my old team did in a sprint, but only if the AI remembers what I told it."
— Solo founder, backend-heavy
The Full-Stack Prototyper
Web today, mobile tomorrow, a browser extension next week. You need a brain that adapts to every stack without re-teaching it your patterns.
"I prototype in React, then port to Swift. My brain has to keep up."
— Product dev, multi-platform
The Solo Team
You are the entire engineering team — planner, implementer, tester, reviewer. Agent teams let you scale without hiring.
"I have /yalla-team review my own code. It catches what I'd miss at midnight."
— Founder-engineer
The Test-Driven Operator
You don't ship without tests. Your brain writes them, runs them, and fixes them automatically inside the pipeline — not as an afterthought.
"Every /yalla run includes tests. Non-negotiable."
— Staff engineer turned indie
The Architecture-Conscious Builder
You care about structure. Production-tested hooks, clean session lifecycle, SQL-backed memory — the boring scaffolding that makes a codebase last.
"The hooks stopped me pushing to main three times this week."
— Senior dev, late career
54%
Never opened a terminal
58%
Non-technical roles
87%
Disorganized files
8/8
Setup friction = #1 blocker
I'm Iwo Szapar. For the past 14 weeks, I sat down with 95 professionals — one at a time, 1-2 hours each — and manually built their Second Brains. What I was really doing was context engineering. That's also what made it impossible to scale.
I was the bottleneck. So I built Second Brain 2.0.
Deliverables that took 3 hours now ship in 15 minutes. Not because AI remembers more. Because AI validates before you review.
Co-founded the AI Maturity Index with Harvard researchers (420,000 data points, acquired by ISG in 2026). Helped 3,000+ companies and 25,000+ professionals at Microsoft, Walmart, and governments worldwide.
Trusted By
How It Tunes for Your Stack
Self-paced. No call needed. Questionnaire → personalized repo → first shipped PR.
Questionnaire maps primary_stack, test framework, CI/CD, review strictness, deployment target.
Primary stack (React/Next/Node/Python/Rails/Swift/Flutter/browser-ext)
Test framework (Vitest/Jest/Playwright/Pytest)
Review strictness (strict adversarial / pragmatic / solo)
Commit cadence (multi-per-day / PR-per-feature / long-branch)
After setup
AI Systems Decay. MemoryOS Prevents It.
New clients, new projects, new preferences — if AI doesn't learn about them, it falls behind. MemoryOS runs decay detection on your SQL database, flagging knowledge items not accessed in 30+ days, tracking confidence scores, and monitoring context pressure across 38 dimensions.
Beyond chat — real PRs
Not Just Chat.
Shipped Code.
Every dev command combines planning, implementation, testing, and review into one action. Type one slash command — get a PR, not a suggestion.
Ship
Solo Pipeline
/yallaPlan → implement → test → review → ship. One command writes the plan, codes the feature, adds tests, reviews with a language-specific reviewer, and opens a PR.
→ PR #442 opened, 0 blockers
Multi-Agent Pipeline
/yalla-teamAdversarial team: planner + implementer + tester + 3 reviewers (Kieran-typescript, security-sentinel, performance-oracle). Runs in parallel. Catches what solo misses.
→ PR #443 opened, 1 blocker: missing MIME whitelist
Tracked Session
/beginCreates a task + session branch + GitHub issue in one command. Hooks block edits on main, so every change belongs to a session.
→ session/task-3363-avatar-upload + issue #1122
PR or Merge
/endPushes the branch, opens a PR (or merges for tiny changes), closes the linked issue, updates the task status. Ends sessions cleanly.
→ PR merged, issue #1122 closed, task done
Intel
Reverse-Engineer a Branch
/schematicPoint at any branch or PR — AI reads the diff, traces execution paths, and writes the spec that would have produced this code. Great for onboarding to legacy work.
→ specs/task-442-avatar-upload.md
Cross-Repo Semantic Search
/recallSearches across every indexed repo + MemoryOS SQL backbone. Finds the rate-limit middleware you wrote 6 months ago in another project.
→ 3 matches: acme-api/middleware/rate-limit.ts + 2 patterns
API Debug Console
/debug-apiTail Vercel logs, replay failed webhooks, inspect the last N requests to an endpoint, diff staging vs prod responses. All from Claude.
→ Last 50 requests to /api/avatar-upload, 2 failures traced
Ops
Safe Migrations
/migrate-databaseWrites reversible Supabase migrations with NOT NULL backfills, foreign key checks, and rollback plans. Runs advisor checks before applying.
→ migration 0042_add_avatar_url.sql + rollback.sql
Pre-Deploy Gate
/validate-buildRuns TypeScript compile, ESLint, unit + integration tests in parallel. Blocks /end if any fail. Keeps main deployable.
→ tsc ok, lint ok, 127/127 tests pass
Security Audit
/security-reviewsecurity-sentinel reviews auth, input validation, secrets handling, CSRF, CORS, and OWASP top 10 across recent diffs. Fresh context, no bias.
→ PASS with 1 warning: rate limit missing on /api/login
12 dev skills. Build your own in minutes.
Every skill is a markdown file. Read it, edit it, duplicate it, or chain it into your own /yalla variant.
Your Data Stays on Your Computer
The Guide is a remote plugin that reads your local brain structure to give guidance. Your actual content, client data, and personal information never leave your computer. We only see which tools you call and how often — for product improvement.
The 5 Layers of Context Engineering
Context engineering isn't one thing — it's a stack. Each layer makes AI smarter about you and your work.
Project Instructions (CLAUDE.md)
A file at the root of your workspace that Claude reads on every conversation. Your preferences, rules, writing style, tool conventions — loaded automatically, every time.
# CLAUDE.md ## Voice: Direct, no fluff. Never use "leverage" or "synergy." ## Clients: Enterprise SaaS, 50-200 employees ## When writing proposals: Use the 3-part framework from /templates
Persistent Memory
AI learns from every conversation and stores patterns, client details, and decisions in a local SQL database with 12 queryable collections and confidence scoring. Month 1: knows your name. Month 6: knows your client's pricing objections, when the last interaction was, and which proposals need updating.
Tool Connections (MCP)
The Model Context Protocol lets Claude read and act on your real dev tools — GitHub (repos, PRs, issues), Vercel (deploys, env vars), Supabase (migrations, logs), Chrome (browser automation for testing). Instead of describing your infra, Claude queries it directly.
Skills & Workflows
Reusable commands like /daily-briefing or /draft-proposal that combine multiple tools and context sources into one action. Type one command, get a complete output that would've taken 30 minutes manually.
Hooks — Deterministic Automation
This is where context engineering gets powerful. Hooks are shell commands that fire automatically at specific points — before a tool runs, after a file is saved, when a session starts. They don't rely on AI judgment. They always execute.
PreToolUse
Block Edit/Write on main branch
branch-guard fires before any code change — forces a session branch
PostToolUse
Auto-log commit to active task
After git commit succeeds, link the SHA to the current /begin session
SessionStart
Load task context + related patterns
When you open Claude, inject the active task + recalled memory
Stop
Extract learnings when queue fills
When session ends with 8+ events queued, run /learn to compound
# Example: Block code edits on main, enforce session branch
{
"hooks": {
"PreToolUse": [{
"matcher": "Edit|Write|MultiEdit",
"hooks": [{
"type": "command",
"command": "$CLAUDE_PROJECT_DIR/.claude/hooks/branch-guard.sh"
}]
}]
}
}The system configures your hooks automatically. You don't write JSON — you tell it what you want enforced.
Most "AI setups" only use Layer 1.
A Second Brain uses all 5 layers working together. That's why the output quality is fundamentally different.
What no other AI tool gives you
Your Database.
Your Infrastructure.
Your Rules.
Every AI wrapper stores your data on their servers. Cancel and it's gone. Your Second Brain deploys on infrastructure you own — Supabase + Vercel, both free tier. Cancel us and keep everything.
Your Own Database
PocketBase (local SQLite) or Supabase (cloud). Your patterns, decisions, test failures, indexed codebases — all in tables you can query with SQL. Not locked in someone else's API.
Your Own Deploy Pipeline
Vercel runs your API endpoints, webhooks, cron jobs. CI runs on GitHub Actions. All on your account — we never see your code.
Your Own Agents
Yalla team, reviewers, implementer, tester — all run locally in your Claude Code. Your code, patterns, and test data never leave your device.
Updates Without Downtime
Skills and agents live in the database, not pinned code. When we ship a better /yalla variant, you get it by updating one row — no git pull, no deploy.
- Data stored on their servers
- Cancel = lose everything
- They control pricing, features, access
- Your AI context locked in their format
- Monthly rent for what should be yours
- Your Supabase database — you have the password
- Cancel us, keep everything deployed
- Open source formats: markdown, JSON, SQL
- 95+ API endpoints running on your Vercel
- One-time build, $0-20/mo to run
SaaS expires. Infrastructure compounds.
What Devs Say
Wouter van den Bijgaart
AI Developer
Replaced DIY setup
"I built my own system and spent 3 hours a week maintaining it. The Second Brain does the maintenance automatically."
Gabe Marusca
Consultant / Dev
20+ hrs/week saved
"Now I type /yalla and ship features I used to spend a day on."
Damian
Product Engineer
Profoundly changed
"The regular AI tools now just seem like child's play. This has profoundly changed how I work."
Pricing
Pay once. Own it forever.
Quick math
97 professionals are running their Second Brain right now. If it saves you 5 hours per week at $200/hr, that's $4,000/month in recovered time. The Kickstart pays for itself in the first week. One purchase. No subscriptions.
For technical users who want full control
DIY
The full system. You set it up.
Full repo: 55 skills, 21 agents, 7 integrations
Setup guide + Health Check MCP
Community access
Self-serve — you configure at your pace
MemoryOS available separately ($199/yr)
No support included
7-day money-back guarantee.
For professionals who want it working today
Kickstart
AI configures it. You're running in minutes.
Everything in DIY
AI agent builds your system from your answers
48-hour priority async support
First year of MemoryOS Pro included ($349 value)
Async support — no calls needed
7-day money-back guarantee.
For leaders who want it built for them
Done-With-You
2-hour onboarding call + full setup.
Everything in Kickstart
2-hour onboarding call with Iwo
I deploy your infrastructure (Vercel + Supabase)
Monthly Second Brain updates (new agents, skills, tools)
12 months MemoryOS included
2-hour call + direct access to Iwo
7-day money-back guarantee.
Your system stays current. Automatically.
New tools and skills ship through MemoryOS. Updates arrive without you doing anything. Health monitoring spots what needs attention. Weekly recommendations tell you what to fix. Included in Kickstart and Done-With-You.
What Happens After You Buy
Get Repo
5 min
Instant email with GitHub repo
Questionnaire
15 min
Answer about role and workflows
Build
~60 min
System generates, configured for you
First Win
7 min
Run /overview, priorities are there
Deploy Infra
30 min
One-click Vercel + Supabase (optional)
FAQ
From the Blog
Learn more about context engineering, MCP, and building better AI systems.
Context Engineering with MCP: A Practitioner's Guide
Deep dive into the Model Context Protocol — what it is, how it works, and why it matters for building AI systems that actually know about your work.
Your Second Brain Is Blind Without MCP
How the Model Context Protocol turns AI memory into AI action. Connecting your Second Brain to Gmail, Calendar, CRM, and more.
From Prompt Engineer to Context Architect
The emerging role nobody trained you for. Why context engineering is the new high-leverage skill for knowledge workers in 2026.
Claude Code Advanced Tips: 6 Months of Engineering Use
Production patterns, hook configurations, and context engineering workflows from 6 months of hardcore use building real systems.
Want to See It First?
Not ready to buy? Watch how it works or try a free resource.
Better System.
Better Output. Every Time.
Stop fighting generic AI. Start with a system that knows you.
DIY
Kickstart — Most Popular
Done-With-You