The JFDI Agentic Development Manifesto

AI That Works With Your Platforms, Not Against Them

The promise of AI-assisted development is being squandered.

Every day, developers paste enterprise code into generic AI tools and receive plausible-looking output that fails on contact with reality. Hallucinated APIs. Invented functions. Patterns that existed in training data but not in production. The industry has accepted a 50% rework rate as normal – and called it “productivity gain.”

We reject this.

JFDI exists because enterprise platforms deserve AI that understands them. Not AI that guesses. Not AI that approximates. AI that knows.

Who We Are

We are engineers. Not prompt writers. Not AI enthusiasts. Engineers.

We’ve been shipping production agentic systems since the technology emerged – not experimenting, but delivering. Our teams are AI natives: professionals who think in human-AI collaboration patterns and have internalised what works and what doesn’t through thousands of hours of real delivery.

That experience is what we bring to your projects.

What We Believe

Platform-native tooling over generic prompting

Generic AI treats Appian like React, Power BI like a spreadsheet, and SharePoint like any web framework. It doesn’t work. We’ve built the tooling that makes it work – MCP servers (integration layers that give AI safe, direct access to platform APIs), linters, evaluators, validation agents – purpose-built for enterprise platforms. When our engineers work on your Appian application, AI doesn’t guess what SAIL syntax looks like; it lints its own code before anyone sees it.

The difference is between describing a platform and giving AI the platform’s development tools.

Knowledge that compounds over knowledge that’s lost

Every AI session starts fresh. Every insight evaporates. Every hard-won lesson must be re-learned. This is institutional amnesia at scale.

Our approach captures what matters: bug fixes, patterns, anti-patterns, architectural decisions, failed approaches. We index it, search it, surface it automatically. When one of our engineers joins your project mid-stream, they inherit the full history of AI-assisted work on that codebase. An anti-pattern discovered in January prevents the same mistake in July – without anyone remembering to mention it.

Knowledge should accumulate, not reset.

Quality by design over quality by hope

“Generate and hope” is not engineering. Every piece of AI-generated work passes through automated gates: tests run, linters check, builds verify, security scans complete. Human reviewers see work that has already proven it compiles, passes tests, and follows standards.

This is an engineering mindset applied to AI-assisted development. Rigour doesn’t disappear because AI wrote the first draft.

Quality is not an aspiration. It’s a checkpoint.

AI as development partner over AI as replacement

We are not building systems to eliminate developers. We are building systems that make our engineers – and yours – radically more effective. AI handles the scaffolding, the boilerplate, the platform-specific incantations. Engineers focus on architecture, business logic, and the decisions that require human judgment.

The goal is not fewer engineers. The goal is engineers who spend their time on work that matters.

AI amplifies expertise. It doesn’t replace it.

Open ecosystems over vendor lock-in

We don’t believe in walled gardens. Our internal accelerators support multiple leading AI models, each chosen for what it does best. We integrate the right tools for your environment: your repositories, your CI/CD, your security requirements. You’re not locked into our systems. You benefit from our expertise.

The best tool for the job should win, not the tool you’re locked into.

Modernisation as transformation over modernisation as translation

Legacy systems don’t need line-by-line conversion. They need re-imagination on modern platforms. We analyse, we understand, we rebuild – with AI that validates output against target platform constraints. Moving from Excel to Power BI isn’t copying formulas; it’s building a proper data model. Moving to Appian isn’t transcribing forms; it’s generating validated SAIL.

Transformation should improve systems, not just relocate them.

What We’ve Built

Our approach isn’t theoretical. We’ve encoded years of agentic development experience into internal accelerators – orchestration frameworks, platform-specific tooling, persistent memory systems, automated quality gates – that our engineers use on every engagement.

This is how we deliver faster without sacrificing quality. This is how we onboard engineers to your codebase in days, not weeks. This is how we ensure that lessons learned on one project benefit the next.

You don’t license our internal tools. You benefit from the expertise they represent.

Our Commitment

We will not ship AI-generated code that we haven’t validated.

We will not claim platform support we haven’t built tooling for.

We will not treat knowledge as disposable.

We will not lock you into systems you can’t extend or escape.

We will not pretend that “good enough” is good enough.

This is JFDI Agentic Development.

AI that understands your enterprise platforms. Knowledge that compounds across your team. Quality that’s verified, not hoped for. Modernisation that transforms, not merely translates.

This is how enterprise AI development should work.
This is how we work.