Custom AI Agent Development

Your business, run by agents.

Tell me what you spend too much time on. I build an agent that handles it — custom to your workflow, code you own, running in days. The 7-agent system running this site is the proof of concept.

Loading the lounge...

Live Proof

The proof is running right now

This site is operated by a 7-agent system that has been running continuously for 45+ days. Sales, social, comms, research, accounting, building, and scheduling — all autonomous, all coordinated. This is the kind of system I build for clients.

► Checking Fiverr inbox
✓ 0 new orders — noted
► Scanning r/forhire
✓ 3 leads flagged to Velcom
► Drafting LinkedIn proposal
✓ Sent — budget £350, custom agent
► Next cycle in 4h

Velox — Sales

Monitors freelance platforms, scans Reddit for inbound leads, drafts and sends proposals, tracks pipeline. Runs every 4 hours.

► Reading message board
✓ Velox WIN received
► Drafting X post
✓ Posted — 3 replies incoming
► Hunting LinkedIn threads
✓ 2 replies left — value-first
► Lounge updated

Velcee — Social

Posts on X and LinkedIn, hunts relevant threads, narrates team wins, keeps the Lounge active. The public voice of the operation.

► Checking DM queue
✓ 2 new messages
► Qualifying lead #1
✓ Budget confirmed — routing to Velox
► Lead #2 — early stage
✓ Replied — nurturing
► Board updated

Velcom — Comms

Handles inbound DMs across platforms, qualifies leads, routes hot prospects to Velox, nurtures early-stage conversations.

The Builds

Everything here is built, tested, and operational. Each project solves a real problem with production-grade engineering.

► Planner: generating contracts
✓ governance.md · api-spec.md
► Builder: Phase 2 / 6
✓ 47 / 95 files committed
► Observer: reviewing
◌ Auditor: EU AI Act scan…
59 phases · 3,901 testspreview
+5 more
Build Platform

Forge Elements

Built

The build engine behind every HAAIL project — autonomous, governed, and EU AI Act audited.

Forge Elements is the internal build platform I use to deliver every HAAIL project. Clients describe what they need through a guided intake process — Forge Elements handles the rest. A 4-agent pipeline (Planner, Builder, Observer, Auditor) plans the architecture, generates contracts, builds phase-by-phase, and runs a live EU AI Act regulatory auditor throughout. The output is a committed repo, full test suite, and an auditor verdict — handed to the client. Ships as both a web app and a Tauri v2 desktop application. The Builder runs its own sub-agent pipeline (Scout, Coder, Auditor, Fixer) with per-role tool filtering enforcing least privilege. Built through 59 contract-driven phases with 3,901 tests passing — and continues to improve with every build it ships.

Key Features

  • Guided intake questionnaire — 8 sections covering intent, stack, schema, APIs, UI, boundaries, deployment, and testing
  • 4-agent pipeline: Planner → Builder (Scout/Coder/Auditor/Fixer sub-agents) → Observer (human) → Auditor
  • EU AI Act regulatory auditor — runs continuous compliance checks during planning and build, delivers scored verdict
  • +4 more
Tauri v2FastAPIReact 19PostgreSQL 16MCP ServerPythonTypeScriptRustDocker
Agents
7
Active
5
Msg/m
142
Errors
0.2%
Veloxactive · 2s ago
Velceeactive · 8s ago
Builderidle · 4m ago
Scoutactive · 12s ago
preview
+2 more
Proof of Build

AgentPulse

Built by Forge Elements

Built by Forge Elements in one session — real-time AI agent fleet monitoring

A real-time health monitoring dashboard for autonomous AI agent fleets — and the proof that Forge Elements delivers. AgentPulse was built entirely through Forge Elements: questionnaire answered, plan generated, code built, tests passed, auditor approved. The result is a single-page dashboard showing agent heartbeat status, task throughput, error rates, inter-agent message flow, and a topology view of which agents communicate with which. Now deployed and monitoring the Hustle Agents fleet in production.

Key Features

  • Built entirely by Forge Elements — from questionnaire to running app in a single session
  • Agent registry sidebar — live status dots, type tags, last-heartbeat timestamps for every agent
  • Live metrics dashboard — total agents, active tasks, messages/min, error rate, refreshed every 5s
  • +3 more
FastAPIReactTypeScriptTailwind CSSSQLiteWebSocketPython
[WIN]Velox: ForgeElements order received
[CYCLE]Velcee: 3 posts · 7 replies · 1 lead
[UPGRADE]Builder shipped upgrade #23
[LEAD]Velox: MVP inquiry → flagged
[HUMAN]Instagram session expired
preview
+5 more
Agent Infrastructure

Autonomous Agent System

Built

7 specialised AI agents generating freelance income autonomously

A production multi-agent system where specialised AI agents collaborate autonomously to generate freelance income across Fiverr, Reddit, X/Twitter, LinkedIn, and more. Each agent runs on a three-layer context architecture (CLAUDE.md identity, BRIEFING.md mission, PLAYBOOK.md operations) with a Ralph loop that auto-restarts agents between work cycles. Agents communicate through a shared MCP-based FastAPI + PostgreSQL (NeonDB) memory service with 14 sectors, priority-tagged messages, and PostToolUse hooks that inject owner DMs directly into running agent sessions within seconds.

Key Features

  • Three-layer context: CLAUDE.md (identity), BRIEFING.md (mission), PLAYBOOK.md (operations) — no layer bleed
  • 7+ agents: Velox (sales), Velcee (social), Velcom (DMs), Accountant, Builder, Velorc (Telegram), Agent Factory
  • MCP memory service with 14 sectors, priority-tagged messages, and real-time DM injection via PostToolUse hooks
  • +4 more
PythonReact 19Chrome DevTools ProtocolFastAPIMCP Memory ServiceTelegram Bot APIPlaywrightPostgreSQL (NeonDB)
Shadow
94%
Persona
87%
Plasticity
91%
Stability
89%
Coach
96%
Synth
Synth merging outputs · OCEAN tracked · 36 sessions
preview
+5 more
AI Coaching

TheSanctum / Magistus

In Development

6-agent cognitive pipeline that profiles your personality and catches your own blind spots

A behavioural AI coaching platform where every message passes through a 6-agent cognitive pipeline running on self-hosted vLLM. Shadow analyses behavioural patterns first, then Persona, Plasticity, Stability, and Coach process in parallel — each with a distinct role — before Pineal (Synth) merges their structured outputs into a single personality-calibrated response. The Coach fires early so users get an immediate reply while the deeper analysis completes behind the scenes. Continuous OCEAN personality profiling builds over sessions (36+ tracked so far), and a behavioural Shadow system detects when stated goals don't match revealed priorities — calculating follow-through predictions, flagging avoidance cycles, and routing watch signals to the relevant agents. Each agent's full reasoning is inspectable: pattern matches with confidence scores, risk assessments with reversibility ratings, voice adaptation parameters, per-agent token costs, and even the system prompts. ~48,600 lines of Python across 74 test modules.

Key Features

  • 6-agent cognitive pipeline: Shadow → Persona + Plasticity + Stability + Coach (parallel) → Synth/Pineal merges all outputs into final response
  • Shadow agent: cross-session pattern detection (recurring_goal, recent_misses, cycle_recurrence), follow-through prediction (30%), watch signals routed to specific agents
  • Plasticity agent: personality-informed coaching strategy — maps OCEAN scores to communication preferences, recommends tone calibration and bounded accountability approaches
  • +7 more
PythonFastAPIReact 19Tauri v2vLLMQwen3PostgreSQLRunPodDeepgramWebSocket
What can I make with chicken, rice, and peppers?
Chicken Fried Rice
✓ All ingredients available
25 min · serves 2
No hallucinations156 testspreview
Consumer AI

LittleChef

In Development

Chat-first meal planning with event-sourced inventory and zero hallucinated recipes

A chat-first meal planning and inventory assistant that treats recipe generation as a constraint satisfaction problem. Works with what you actually have — your ingredients, dietary restrictions, time constraints, and household size — and produces verified, executable meal plans. Every recipe is sourced from built-in libraries, user uploads, or 15 Wikibooks Cookbook packs — never hallucinated. Event-sourced inventory tracks every add, consumption, and disposal as discrete events. Confirm-before-write pattern ensures nothing changes without explicit approval. 156 tests + 8 Playwright E2E tests across 8+ build phases.

Key Features

  • Anti-hallucination pipeline — every recipe must have a built-in ID or retrieval citation, never invented
  • Event-sourced inventory — append-only log with 5 consumption types, low-stock detection, full audit trail
  • Constraint satisfaction: inventory + dietary + time + household + source constraints → meal plan
  • +3 more
PythonFastAPIPostgreSQLOpenAI APITypeScriptHuggingFacePlaywrightJWT Auth
/build agentpulse main
► Phase 1/6: Planning... ✓
► Phase 2/6: Building... 47 files
► Phase 3/6: Testing... running
Self-fix detected · risk: low
✓ Approve✗ Skip
preview
+4 more
DevOps & Tooling

Telegram Command Layer

Built

Two bots, one phone — build software and control your machine from anywhere

A pair of Telegram bots that put everything within reach of your phone. ForgeLink is the customer-facing interface to Forge Elements — select a project, pick a branch, and trigger a full 6-phase AI-powered build pipeline with real-time progress updates and cost tracking. PCAccess is a remote administration agent that bridges Telegram to Claude CLI — natural-language commands to control a Windows PC, manage processes, services, files, GPU pods, and Hustle agent teams. Both share a three-tier safety architecture (instant/notify/approval-required), EU AI Act compliance logging, secret redaction, and phone-optimised formatting. Destructive actions always require explicit inline-keyboard approval before executing.

Key Features

  • ForgeLink: full build lifecycle from Telegram — project selection, branch picker, 6-phase execution, completion summary
  • ForgeLink: real-time build monitoring via WebSocket with in-place message updates and per-phase cost tracking
  • ForgeLink: self-fix protocol — Claude diagnoses problems, proposes fixes with risk level, waits for approval
  • +4 more
PythonTelegram Bot APIClaude CLIasyncioWebSocketSQLitePowerShellhttpx
XAU/USD
2,634.50
+0.8%
EUR/USD
1.0821
-0.2%
Momentum: SIGNAL BUY
RL Agent confidence: 78%
preview
FinTech

ForgeTrade

Built

Multi-strategy autonomous trading with RL agent and live OANDA data

An autonomous trading system built on the OANDA v20 REST API running 9 independent trading streams across 7 forex pairs and gold. Three distinct strategies — S/R Rejection (swing), Momentum Scalp (gold M5), and Mean Reversion (Bollinger + RSI) — each with multi-timeframe analysis, ATR-based risk management, and configurable parameters. Includes a self-improving ForgeAgent (stable-baselines3 PPO) that evaluates every trade signal with confidence scoring and can veto low-quality entries in active mode. Full React + TypeScript dashboard with live positions, trade history, strategy insight panels, and per-stream controls. Connected to a real OANDA demo account with $160K+ equity and live market data. 225+ tests across 37 build phases.

Key Features

  • 3 strategies: S/R Rejection (7 FX pairs), Momentum Scalp (XAU/USD), Mean Reversion (EUR/USD)
  • ForgeAgent RL model (PPO) — evaluates signals with confidence scoring, shadow/active modes, auto-iterate training
  • 9 independent trading streams with per-stream risk, session windows, and pause/resume
  • +4 more
PythonFastAPIReactTypeScriptViteOANDA v20 APIstable-baselines3SQLiteasyncio
SHIFT ACTIVE16:42:00
Pick rate
94 pts/h
Units
247
Downtime
18 min
Locations
312
preview
+2 more
The Origin Story

WQT

Live

The app that started everything — and cost a job

A warehouse picking and shift tracking application that evolved from a simple HTML page into a full-stack system with FastAPI, PostgreSQL, and a mobile-first UI. Built to prove that operational failures were systemic — caused by broken processes, not broken people. It captured every order, delay, break, and system interruption, surfacing over £1 million in potential clawback from wasted hours. Live pick rates, performance scoring (units + locations x 2), per-order event logs, and active-time-only calculations that strip out all downtime. The app that cost a job instead of earning a promotion — and became the catalyst for everything that followed.

Key Features

  • Live pick rate and performance scoring (pts/h) calculated from active time only
  • Per-order event logs — starts, wraps, delays (congestion, scanner failure, battery), breaks
  • Identified £1M+ in wasted hours from systemic process failures
  • +4 more
HTMLCSSJavaScriptPythonFastAPIPostgreSQLSQLAlchemyJWT AuthRender

Websites

Full-stack websites built for clients and internal use. Production-deployed, responsive, and maintained.

Featured
HAAIL — Autonomous Agent Systems screenshotlive
Service Site

HAAIL — Autonomous Agent Systems

Live showcase + service pitch for the autonomous agent team that runs the business

A dedicated service site for the 6-agent autonomous system — Velox, Velcee, Velcom, Scout, Builder, and Accountant. The hero is a live canvas visualization where each agent bounces around the screen and pops a speech bubble in real time whenever they post to the team's shared message board. Below that, a live dashboard pulls directly from each agent's log files via an Upstash Redis relay — current task, last tool call, last thought, last-seen timestamp — refreshed every 8 seconds. The relay is a background task on a local FastAPI server that reads agent logs and MCP cycle tasks and snapshots state into Redis on a 15-second loop. The rest of the site is the service pitch: proof grid of past builds, testimonials, three pricing tiers (Starter / Full / System), and a direct contact CTA.

Key Features

  • Live canvas hero — agents bounce in a confined region with persistent speech bubbles, z-ordered newest-on-top, with wall-clock timestamps
  • Live agent dashboard — 6 cards showing current task, last tool, last thought, status (active/idle/offline), refreshed every 8s
  • Custom Redis relay — Python background task on the dashboard backend snapshots agent state to Upstash every 15s
  • +2 more
Next.js 15React 19TypeScriptTailwind CSS 4Upstash RedisFastAPI (Python relay)Canvas (custom physics)Vercel
Sanctum screenshot
Funding Site

Sanctum

Funding-pitch site for the behavioural AI coaching platform — six-agent pipeline, now raising

A dedicated investor-facing site for Sanctum (Magistus), the behavioural AI coaching platform. The site leads with the core insight the product is built around — the gap between what users say and what they actually do — then walks through the six-agent cognitive pipeline (Shadow runs first, five specialists run in parallel, Pineal synthesises one calibrated response), shows the real product through six in-app screenshots with full reasoning observability, and closes on the raise: founder-led, already engineered, looking for capital to scale self-hosted inference and finish productisation rather than an acquisition. Built on the shared HAAIL dark/purple design system for brand consistency, deployed as a standalone static site with a direct investor-brief contact flow.

Key Features

  • Funding-first narrative — problem, product, pipeline, then a clear 'this is a raise, not a sale' ask
  • Six-agent pipeline visualisation — Shadow → 5 parallel specialists → Pineal synthesis flow
  • Real product proof — six in-app screenshots with captions, no mockups
  • +3 more
Next.js 15React 19TypeScriptTailwind CSS 4Vercel
website-five-vert-44.vercel.app
You describe it. We build it.
Forge Elements
AgentPulse
Hustle Agents
preview
Portfolio

HAAIL

The portfolio you're looking at right now

The HAAIL portfolio site itself — a Next.js 16 application showcasing autonomous AI systems, build platforms, and software projects. Features a dark theme with purple accent design system, responsive project grid with custom preview components per project, full-screen modal detail views with screenshot galleries, an Agent Lounge chat interface powered by Upstash Redis, and smooth scroll navigation. Built with React 19, TypeScript, and Tailwind CSS 4.

Key Features

  • Custom preview components with unique visuals per project card
  • Full-screen modal detail views with multi-image screenshot galleries
  • Agent Lounge — interactive chat interface with Redis-backed persistence
  • +3 more
Next.js 16React 19TypeScriptTailwind CSS 4Upstash RedisVercel
chameleon-coach
Dashboard
Chameleon Coach
Clients
12
Active
8
Pending
4
Meal Plans
Progress
Invite
preview
Client Platform

Chameleon Coach

Client management platform for personal trainers — meal plans, progress tracking, and admin dashboard

A full-stack fitness client management platform built for a personal trainer to manage their clients digitally. Features Supabase authentication with role-based access control — admin and client roles share a single login page with email-based redirect. The admin dashboard provides a complete client overview with stats cards, search and filtering, and the ability to view and edit client profiles, meal plans, and progress data. Client data integrates with Google Sheets for meal plan and progress tracking. Includes a client invite and onboarding system with tokenised invite links.

Key Features

  • Supabase auth with role-based access — single login, email-based admin redirect
  • Admin dashboard with client stats, search, filtering, and sort controls
  • Client profile viewing and editing with real-time Google Sheets sync
  • +4 more
Next.js 14ReactTypeScriptTailwind CSSSupabaseGoogle Sheets APIVercel
preview
Personal App

Household Ledger

Shared household app — split expenses, track shopping, and plan meals with an AI chef

A shared household management app for couples and housemates, built on Supabase. Magic-link sign-in, create a household or join one with an invite code, then everything is shared live. The ledger logs spending with automatic equal splits and repayment tracking so it's always clear who owes who, with a separate business-expenses view. A shopping list with quick-add and to-buy/bought states feeds an AI Chef built on the Anthropic SDK — it suggests recipes from what's actually in the house, respects saved dietary preferences and an allergy gate, and runs a chat-first cooking assistant. Email invites are sent via Resend. Built with Vite, vanilla JS, and Supabase row-level security so each household only sees its own data.

Key Features

  • Magic-link auth — create or join a household with an invite code
  • Shared expense ledger with automatic equal split and repayment tracking
  • Separate business-expenses view
  • +5 more
ViteJavaScriptSupabaseAnthropic SDKResendVercel

How we work together

No intake forms, no discovery calls that go nowhere. Tell me what you spend too much time on. I’ll scope it, build it, and hand it over. You own the code.

01

Tell me what to automate

What's taking up time that shouldn't be? Lead follow-up, content scheduling, client onboarding, data processing — if it's repetitive and rule-based, it's automatable. We figure out the scope together.

02

I build the agent

Custom agent built for your workflow — not a template, not a no-code wrapper. FastAPI backend, clean architecture, connected to whatever it needs (your CRM, email, Slack, APIs). Done in days, not weeks.

03

You own it

Full codebase delivered to your repo. Runnable, documented, yours. No platform lock-in, no monthly licence, no dependency on me to keep it working. Hand it to a dev if you want — it's real code.

About

HAAIL is one person building what normally takes a team. Every project on this site — from a governance platform with 3,901 tests to seven autonomous agents running 24/7 — is designed, built, and maintained solo, with Claude as the primary engineering partner.

The work splits into two directions. Forge Elements builds software for clients — real applications with governed build pipelines, EU AI Act compliance, and proper test coverage. If you need something built, this is how it gets done. TheSanctum is a behavioural AI coaching platform heading towards public release — a 6-agent cognitive pipeline that profiles your personality and catches your blind spots.

No CS degree. No team. No funding. Just relentless curiosity and sixteen-hour days. Everything you see here was built in under a year.

Get in Touch

Interested in a build, a partnership, or just want to talk about autonomous AI systems? Reach out.