For product software company executives
The board's asking about it, your engineers are already experimenting, and you're left deciding whether it's a tool to buy, a hire to make, or something else.
Most teams start with the tools. That's backwards, and it's why so little actually changes.
The hard part of software didn't go away. The expensive part did.
Writing code got cheap. Deciding what to build, proving customers want it and owning the call didn't get any easier. Hand your engineers the tools and leave everything else alone, and you just build the wrong things faster.
What it looks like when AI gets treated as a tool
"We rolled out AI coding tools. I can't point to what got cheaper."
The tools write code faster. The process around the code didn't change, so the cost just moved somewhere else.
"Everyone's using it differently."
Some engineers live in it, some ignore it, and nobody's steering it toward the work that matters. That's a leadership problem, not a tool problem.
"Our AI bill keeps climbing."
Without a budget and some guardrails, spend grows with usage, not with results.
"It writes code that doesn't fit our system."
Point AI at a big codebase nobody scoped for it and it starts guessing. On tangled systems it has to talk through the design before it writes anything.
Recognize one of these? Let's see what you'd save.Free · 30 minutes · A straight answer either way
See what you'd saveWriting code was always the most expensive part of software. It was never the hardest. So we rebuild how work moves from idea to production, and the whole team moves up with it.
PMs stop writing tickets. They build working proofs of concept, put them in front of customers almost right away, and come back with real answers before anyone builds the real thing.
Once an idea's proven, senior engineers run several AI agents in parallel to build it. Complex changes get a design round with the architect first, and juniors take on smaller, well-defined pieces.
Everyone gets the tools, scoped to their role and pointed at real business problems. AI spend runs on a budget someone owns, and everyone, from the executive down, comes out working at a higher level.
What you do with the extra capacity is your call.
Find out which column you're in.Free · 30 minutes · A straight answer either way
See what you'd saveOne engagement, the same shape every time. For those 90 days it's the top priority, and nothing on the roadmap gets in its way.
In the first week we map how work really flows, how your architecture fits together and what it all costs today. Then the guardrails go in, AI gets scoped to your codebase, and a pilot team ships its first real work the new way.
PMs start testing ideas with customers before anything's built, and engineers run AI agents on the work that's proven. Bug triage goes AI-first, and the rollout spreads past the pilot team.
The team's new shape gets set, AI spend gets an owner, and the people who run the process write it down. You see what it's saving against where you started.
Nothing's held back. You keep the setup, the written process and the playbook.
The track record behind Averware comes from running software organizations, not advising them. One connected-device platform went from zero to 30 million devices and $320M in annual product revenue, and engineering was led through a $1.4B acquisition without breaking delivery. That's the lens we bring: what's worth building, what it costs, and who owns it.
Executives and peers who saw the work up close.
Graham is a leader that positions his team members for success and opportunity. He extends himself not only to Products and Services, but also across Marketing, IT, Product Support, and Finance — in doing so he helps raise the entire organization. Whether you're on Graham's team or connected with him in any way, you're going to get his full attention.
Graham's leadership and clear thinking are true assets. He drove the implementation of a new eCommerce platform that facilitated nearly 75% of company revenue, and took on software development leadership for the company's innovative IoT platform. His leadership skills are highly regarded by teammates and the executive team. I highly recommend Graham to any company.
Graham has both excellent technical and business understanding — allowing him to align his teams with larger business goals while understanding the finer points of complex technical architecture. Graham leads with a calm and embracing demeanor which grows great trust. Graham and I never had a bad day working together, even on the most trying projects.
AI makes coding cheap. It doesn't fix the process. These are process problems we've fixed, and AI-assisted engineering makes that kind of fix faster now. Company names aren't published here. Ask on the call and we'll tell you what we can.
A subscription business sat inside an 80,000-unit/year hardware platform. It was invisible to customers, underpriced, and had no renewal path or dealer incentive to sell it. The product hadn't failed. It had been neglected.
Growth came from fixing pricing, incentives, renewals and customer reach, not launching a new product.
A $20M software company's post-acquisition integration stalled. Product ownership was ad-hoc, trust between teams was low, and the company was expanding into multiple states at once. Complexity was compounding faster than capacity could absorb it.
Faster growth came from narrowing scope, rebuilding product discipline and modernizing the platform.
A $2–3M software company was losing money with no visibility into why. Software spend had grown undisciplined, projects took 3–4 months, and there was no P&L link between spend and outcome.
Profitability came from building the P&L, cutting software sprawl and installing a repeatable delivery process.
All companies anonymized. Results available upon request. Some of this work predates AI tools, and the pattern hasn't changed.
Everybody levels up.
This is a different way of working, and it reaches the whole team, from the executive to the newest engineer.
We take a small number of teams at a time. If you're ready to make this the priority, start with what you'd save.