2024–Present
LEAP Legal Software
AI Practice Management Engineering Lead
Created a no-code AI agentic platform for legal firms, transforming how legal professionals manage matter profitability.
I’m Dale, an entrepreneur and engineer turning ambitious ideas into useful products.
Co-founder of Avenue Bank and CreditorWatch. Now building AI solutions.
01 / Experience
From credit risk and banking to the next generation of AI tools.
2024–Present
AI Practice Management Engineering Lead
Created a no-code AI agentic platform for legal firms, transforming how legal professionals manage matter profitability.
2018–2024
Co-founder, COO & CDO
Secured $77M+ in funding, obtained a full banking licence in 2024, and built 24-hour processing systems to improve the customer experience.
2010–2018
Co-founder, CTO & Innovation Director
Led technology and product from startup to successful exit, pioneering AI risk scores and better credit risk assessment.
02 / Approach
Turn ideas into working prototypes. Test early, learn from real users, and iterate.
Apply AI to complex business processes, making more room for the work that matters.
Combine technical depth with commercial thinking to build useful, sustainable products.
03 / Open source
Practical AI tools for the PHP community.
A complete PHP client for Claude, with streaming, tool use, vision, and extended thinking.
Build autonomous AI agents with planning, tool orchestration, and multi-provider support.
Autonomous agents and AI-powered workflows for the Laravel ecosystem.
A CLI AI assistant with cost-aware routing and on-device Apple Intelligence support.
Orchestrate models from multiple AI providers in a single pipeline.
Facades, service providers, and configuration for Claude in Laravel.
Learn modern PHP by building real applications. Completely free.
05 / Writing
Thoughts on AI, technology, and entrepreneurship.
A short write-up on using Cursor, Kimi K2.5, Laravel, React, and shadcn/ui to test whether a tightly planned agent loop can build a useful app cheaply.
In the AI age, output volume is no longer a useful proxy for value. The new standard is signal quality: clarity, precision, and decisions that move work forward.
AI coding models and agents are powerful, but they still need tight supervision. Here is the process I use to keep quality high and avoid costly drift.
Have an ambitious idea or an interesting problem? I’m always open to a conversation.
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