Use
AI feels too hard
Start with one real task and learn enough to make an informed choice. You do not need to pretend anyone can do this effortlessly.
AI for businesses and software teams
AI accelerates, but moving fast is not the same as moving forward.
I'm William Hallatt. I work with business owners, operators, and software leaders to deliver evidence-led AI transformation and automation programs. If you're unsure if it's working, it probably isn't. Measure and prove progress. Don't guess.
Skip the reading · Let your AI do the work
Your AI can help you assess my offer to see if we should talk.
Copy this prompt into Claude, ChatGPT, or Cursor. It asks three questions, one at a time. Then it tells you straight whether to write to me — even if you are not sure what you need — try a simpler step, or look for someone else. If a conversation would help, it drafts a short note you can send me.
What I Do
Three ways to work together
01
You Don't Know the Details, but You Know What You Want!For Businesses: Practical AI & Automating Everyday Work
Automating how you work is no longer reserved for companies with engineering departments or six-figure agency budgets. AI puts focused, purpose-built tools within your reach. I can teach you how to use AI to build software for yourself, or I can do it for you. Either way, once you see what's possible, you'll look at inefficiencies and irritations in your daily life with fresh eyes.
Read on
02
You Thought You Knew What Was Going On, but Now You're Not Sure.For Professional Software Teams: AI-First Software Product Development
AI amplifies the product-development system you already have. If your product development and delivery system cannot test hypotheses or measure value quickly, adding AI only produces unverified code faster. I work with engineering and product leaders to design the controls, vertical slices, and agent workflows required to turn AI leverage into working software and verified value.
Read on
03
You Feel Something's Missing, but You Can't Put Your Finger On It.For Technical Leaders: Leadership Training & Coaching
Leadership is a deep, nuanced topic. There's no one right way, but there are fundamentals that you must know and understand if you wish to be an effective leader. Training builds the theoretical foundation. Coaching helps you bridge the knowing-doing gap.
Read on
For Businesses: Practical AI & Automating Everyday Work.
You do not need to become a software engineer, but you do need to decide if you want to invest the effort to become capable yourself, or buy experienced help to build with you.
Common Scenarios
Use
I am experimenting but stuck
Turn trial and error into a deliberate working practice with feedback and judgment.
Connect
The tools do not talk to my systems
Connect AI to email, documents, knowledge and existing software with appropriate controls.
Build
No packaged product fits
Build focused software only when the workflow is valuable and distinctive enough to justify it.
Review
I already made a prototype
Review whether it can become a viable, trustworthy product rather than adding features blindly.
Wait
I am not sure this is worth doing
Wait is a valid outcome. Clarify the problem and gather evidence before spending money.
Learn to build it, or pay for the build.
I show you how
Build Capability
I provide training and practical support focused on your business, so you learn how to use AI to build custom software for your unique problems (without having to become a software engineer).
Can you teach me to build with AI if I'm not technical?
Yes. Expect effort, trial and error, and a shift in how you describe problems and judge results, but yes. Absolutely.
Best for when you want internal competence and long-term independence.
I do it for you
Just the leverage
I connect, automate or build focused software for you when packaged off-the-shelf tools fall short, cost too much, or you didn't even know software could help.
Do I need custom software?
Usually not at first. We'll start with better use of existing tools, then integrations, and build only when justified.
Best for when you want the operational outcome without doing the learning or work yourself.
Start with the problem
Use before connect. Connect before build.
The least expensive intervention that genuinely solves the problem is usually the right one.
01
Use
Learn to use capable AI tools against the work you actually do: thinking, writing, decisions, documents and customer communication.
Best when the obstacle is capability, not missing software.
02
Connect
Link AI to email, documents, business systems, knowledge and practical communication channels so useful work can happen in context.
Best when the tools exist but the plumbing does not.
03
Build
Create focused software around a specific operational problem when packaged products cannot serve it well.
Best when the problem is distinctive enough to earn custom code.
The AI Bottleneck Trilemma
AI is fast, but you can't blindly trust it—and putting a human in the pipe creates a bottleneck.
Compare the three ways organisations wire humans and AI together:
02 · Human-in-the-Loop
Wherever you put a human inside a swarm of agents, the human becomes the bottleneck.
Because you cannot blindly trust the output, you put a person in the pipe to review every draft, PR, or action before it ships. The entire system slows down to one person’s reading speed. Work queues up behind the reviewer until they burn out or start rubber-stamping.
Where does that leave you?
Stop using humans as item-by-item spellcheckers for agents. Design the slice size, automated checks, and value evidence so the system carries the load.
"Just add AI."
I also haven't quite figured out how to build a billion dollar business with autonomous agent swarms that work while I sleep. I have, however, seen how strengthening core product-development and delivery fundamentals throughout an organisation, rethinking workflows from the ground up, and figuring out how to test and measure progress lead to positive AI leverage.
Cause 01
Weak fundamentals.
At its most basic, your product development and delivery system is a hypothesis-testing loop. We rarely know for sure if a change/feature will add value to a user (product), or to the team (productivity) and we don't want to waste money if we're wrong. So first prize is to always build and ship the smallest (lowest dev cost, lowest risk, minimal loss if we're wrong), highest value (often qualitative guesswork, it's an art) slice of work. And then we need to do this over, and over, day after day.
It turns out all of this is bloody hard.
The point is that your best chance is small tests, frequent shipping, rapid iteration. That is the heart of agile and continuous discovery.1 Small, small, small. Cut scope. Reduce complexity. It's much harder to remove than to add even as humans, and AI loves doing more, so if you don't already have this nailed down, adding AI into the mix will absolutely bring you a lot of pain extremely quickly.
More software is not the same as more value.
The AI Bottleneck Trilemma
AI is fast, but you can't blindly trust it—and putting a human in the pipe creates a bottleneck.
Compare the three ways organisations wire humans and AI together:
02 · Human-in-the-Loop
Wherever you put a human inside a swarm of agents, the human becomes the bottleneck.
Because you cannot blindly trust the output, you put a person in the pipe to review every draft, PR, or action before it ships. The entire system slows down to one person’s reading speed. Work queues up behind the reviewer until they burn out or start rubber-stamping.
Where does that leave you?
Stop using humans as item-by-item spellcheckers for agents. Design the slice size, automated checks, and value evidence so the system carries the load.
Cause 02
A new way of working, forced into an old shape.
If you bolt agents onto a system designed around humans, what you'll get is an amplified version of the same organisation.
“AI-first” means redesigning work around AI's strengths, i.e. what you should stop doing. It requires a mindset shift not dissimilar to what I've seen when individual contributors move into their first leadership roles. There are things you need to learn how to let go of, so that you are not the bottleneck.
You need to learn a new way of working, with an old technique.3
Cause 03
Not knowing how to test and measure value.
“If you don't know where you're going, any road will get you there”.
Token use (don't do this), training attendance, lines of code produced (definitely don't do this), time saved. Those can all go up while revenue, quality and delivery stay put.
Value evidence is a baseline and a way to see whether your experiments produce the results you wanted. Without that, you cannot tell a useful change (outcome) from a busy one (output), which makes it really difficult to decide whether to keep, revise or reverse what you just did.
Good luck measuring knowledge worker productivity directly. No single number can tell you whether what you're doing is working. The best we have, outside of increased profitability, are proxies. But at least we have proxies. And nothing stops us from coming up with or refining specific metrics you care about.4
An AI-Native Playbook
Below is one way to think about human and AI collaboration across the product lifecycle: form a hypothesis, ship the smallest slice that can test it, and learn.2
01
Selected stage
Intent & Discovery
What AI is good at
Sort and summarise the research you give it, surface themes, draft interview guides and generate options worth testing.
What people still decide
Stay close to customers. Write a hypothesis small enough to test, define what better means and decide whether the evidence is good enough to invest.
What to look at
A testable hypothesis, observed customer or engineering behaviour, and a clear intended outcome.
What happens in production becomes evidence for the next hypothesis. Then the cycle starts again.
Double-loop learning
Select any part of the loop below:
Footnotes
What's the first thing you look at when you start an inquiry?
Leadership -> Culture -> Cognitive LoadLeaders are developed.
Before you can understand, you must know, but knowing isn't the same as doing. Training builds the theoretical foundation and coaching helps you bridge the knowing-doing gap.
The challenge
It's a totally different job
High-performers are promoted because they excel in their craft. Yet most step into leadership roles with little support, training, or recognition that the transition from individual contributor to leader is difficult.
Technical brilliance doesn't automatically translate to leadership effectiveness. When you're used to being the one with the solutions, letting go can be hard, but the longer you hold on, the more of a bottleneck you become and the less effective you are as a leader.
If this sounds familiar, whether you're experiencing it yourself or seeing it in your leadership team, that is what training and coaching address. When leadership is treated as a discipline, leaders amplify their teams.
The fundamentals
Leadership Training: The Mechanics & The Hard Stuff
Leadership is a systems discipline with observable mechanics. My training focuses on core mental models and difficult interpersonal practices.
01
From Solver to Multiplier
Experts solve problems directly; leaders design conditions for others to solve them. Learn when to switch between managing authority and coaching inquiry to stop becoming the team bottleneck.
02
Feedback without Evasion
Pairing personal care with direct challenge (Radical Candor). Drill fast, behavioural feedback loops that address reality in the moment, breaking the “ruinous empathy” trap.
03
Productive Conflict
Breaking artificial harmony and corridor politics. Mine for conflict, separate ideological debate from personal identity, and introduce structured critique tools to debate ideas vigorously.
04
Systemic Accountability
Replace vague expectations with explicit contracting. Use the Ladder of Leadership to move teams from “tell me what to do” to “I intend to”, building real peer standards.
Delivery Formats
Modular Half-Day Workshops
Focused deep-dives on individual topics, delivered flexibly around team schedules.
1–2 Day Leadership Intensives
Immersive sprints for leadership groups to align on common language and operational standards.
Evidence-based practice
Evidence-Based Leadership Coaching
A coach helps you get from where you are to where you want to be — not through therapy or pre-packaged advice, but by creating the structured reflection and inquiry needed to bridge the knowing-doing gap.
Partnering to turn insight into observable behaviour change.
As an International Coaching Federation (ICF) Associate Certified Coach (ACC), I practice coaching grounded in behavioural science, adult development theory, and goal-setting literature. It is client-centred and solution-focused: rather than lecturing, I partner with you to clarify goals, interrogate limiting assumptions, and establish concrete action contracts.
✓ ICF ACC Credentialled✓ Objective feedback & accountability✓ 1:1 confidential sparring partner
Tangible Outcomes
Decision Clarity & Focus
Cut through operational noise to focus on high-leverage strategic priorities and systemic bottlenecks.
Expanded Behavioural Range
Move fluidly between directive authority and developmental inquiry when under pressure.
High-Trust Team Climate
Foster genuine psychological safety, productive debate, and clear peer accountability.
Sustained Performance Loop
Regular sprints ensure newly developed leadership practices survive contact with daily delivery.
01/05
What stands out most about Will's approach is the profound sense of trust he fosters in every session. He has a way of turning silence into a powerful tool that makes me feel safe enough to explore the real challenges I'm facing. He is a considered, pragmatic guide who helps me find my own answers by helping me go past the surface-level thoughts and tackle the core of what needs to be addressed. An exceptional coach in every sense, with an awesome sense of humour and humanity.
What's the difference between training and coaching?
There's nothing wrong with theory and frameworks. But theory rarely survives first contact with the real world. Coaching isn't about handing people more models or filling in skill gaps on a competency matrix. It's about helping people wrestle with the complexity of their own context and apply what they know in ways that work.
Read: Coaching, the overlooked link in leadership developmentThe AI Bottleneck Trilemma
AI is fast, but you can't blindly trust it—and putting a human in the pipe creates a bottleneck.
Compare the three ways organisations wire humans and AI together:
02 · Human-in-the-Loop
Wherever you put a human inside a swarm of agents, the human becomes the bottleneck.
Because you cannot blindly trust the output, you put a person in the pipe to review every draft, PR, or action before it ships. The entire system slows down to one person’s reading speed. Work queues up behind the reviewer until they burn out or start rubber-stamping.
Where does that leave you?
Stop using humans as item-by-item spellcheckers for agents. Design the slice size, automated checks, and value evidence so the system carries the load.
Want to work together?