Nathan Killick's first pilot at Definely converted one license. From a firm he already knew. After four months in the role. He sat with that result, mapped exactly what broke, built a repeatable process from scratch, and hit over 100% of target in his first full year. His pilot conversion rate since then? 90-95%.

That turnaround didn't come from the product. Definely is a great product. It came entirely from process, mutual action plans, Gantt charts, stakeholder mapping beyond the C-suite, and an obsessive checklist he runs on every single pilot without exception.

In this episode Nathan breaks down the full GTM picture: why law firms start pilots wanting to buy and how vendors kill their own deals; how he grew US revenue from 1% to 30% without a US office; why the SDR and AE functions at most LegalTech companies are structured wrong; how he automated 75% of his pilot process using Claude and MCP; and why the value calculator he built using Thomson Reuters data changed every business case conversation he has.

He also talks about what Freshfields going all-in with Anthropic signals for the broader market, why best-of-breed is starting to win against all-in-one, and the one question every early-stage LegalTech founder needs to answer before their next hire: if Harvey or Legora can absorb what you do, what's your moat?

If you're building or selling in LegalTech right now, this is the most commercially honest 45 minutes available on what GTM actually looks like in 2026.

Timestamps:00:00 — What top law firms are saying about AI right now00:44 — Build vs buy: Kirkland Ellis, Freshfields, Harvey, Legora03:22 — How Definely's GTM motion changed as AI took over drafting05:30 — Why you can't use AI to verify its own output07:23 — The independent verification layer law firms actually need08:15 — What the first conversation with a top 50 firm partner sounds like10:21 — Pilot process: why vendors kill their own deals13:30 — Honesty upfront: naming what you can't do before the pilot starts13:30 — Treating pilots as a project: Gantt charts and mutual action plans15:49 — One license. Then 90-95% conversion. What changed.16:13 — Building a repeatable pilot process from a failed first attempt18:36 — US expansion: 1% to 30% revenue without a US office18:36 -- Iltacon and conference-led relationship building21:00 — Stakeholder mapping beyond the obvious C-suite25:00 — Nine AI tools connected via MCP: what that looks like in practice27:00 — Data hygiene: why you can't put client data in free ChatGPT29:30 — Account coverage going from 40% to 80% with AI assistance31:20 — CRM updates: from 1 hour to 10 minutes with automated MEDDIC mapping33:20 — Meeting prep automated via Claude and Google Calendar35:42 — Where AI should and shouldn't sit in a LegalTech sales motion37:30 — The value calculator built using Thomson Reuters and Pursuit data39:56 — Final advice: find your moat before Harvey and Legora find it for you39:56 — When to hire a VP of Sales vs staying in founder-led sales44:40 — Closing thoughts

🎙️ Taking LegalTech to Market is hosted by Paul Church, LegalTech recruiter, talent advisor, and one of the most listened-to voices in the space.

Subscribe for new episodes every week.

One license. From a firm he already knew. After four months in the role.

Nathan Killick didn't spin it. He sat with the result, identified exactly what broke, and built a process so repeatable his pilot conversion rate hit 90-95%.

In this trailer: why vendors kill their own deals, why copying everyone else's GTM playbook is a losing strategy, and the one question every LegalTech founder needs to answer right now, if Harvey or Legora can absorb what you do, what's your moat?

Full episode live tomorrow. 🎙️ Taking LegalTech to Market.

Nick Holzherr spent millions of pounds on legal fees building and selling businesses, including selling Whisk to Samsung. That experience didn't just give him a product idea. It gave him a perspective on the law firm business model that most people in legal are too close to see clearly.

80-90% of what you pay in a legal bill is overhead. AI makes that overhead free. But law firms are structured in a way that makes it almost impossible for them to pass those savings on. Which is why Nick didn't build GitLaw for law firms. He built it for the businesses that use them, and priced it at $20 a month with a free tier, no demos, no sales calls, and no salespeople.

In this episode Nick breaks down the full GTM model: why your real competitor in the SMB legal market isn't Harvey or Legora, it's ChatGPT and Claude; why activation is the only metric that matters when the product is self-serve; how referral-led growth works when every document you send is an invite opportunity; and why he thinks people hire sales teams far too early.

He also talks about the wrapper question every LegalTech founder is privately obsessing over, why a 15-person team can do the work of 100 with agents, what the LegalTech pricing stack looks like in 2027, and the one hiring framework that changes who gets interviewed for every commercial role.

If you're building, selling, or investing in LegalTech, this is one of the most commercially honest conversations about where the market is going.

Timestamps:00:00 — Introduction00:50 — Why GitLaw sells to businesses, not law firms01:03 — Spending millions on legal fees: the personal problem01:03 — 80-90% of a legal bill is overhead. AI makes it free.03:39 — Positioning against ChatGPT and Claude, not Harvey or Legora03:57 — Why DIY legal AI gets you to court05:30 — Templates, human-reviewed forms and how GitLaw reduces hallucination06:54 — Will lawyers still be needed in five years?07:14 — The AI 2027 question and why Nick is genuinely scared08:21 — The law firm pyramid: juniors charged out at 5x their salary10:02 — Senior lawyers privately asking Nick about their pensions12:36 — What qualified pipeline looks like with no sales team12:58 — Activation is the bottleneck, not acquisition or conversion16:06 — Will GitLaw ever have a sales team?16:13 — Referral-led growth: how DocuSign, Dropbox and Calendly did it17:35 — How AI agents run GTM operations at GitLaw18:10 — The Slack agent that knows everything about the business22:38 — 15 people doing the work of 100 with agents23:33 — The wrapper question: good AI wrapper vs bad AI wrapper26:49 — Context, garden tending and taste as durable competitive advantages29:49 — GitLaw from 10 to 25 people: what triggers it32:07 — What LegalTech GTM looks like in 202734:56 — Best GTM decision of the last 12 months: hiring AI native people35:37 — Worst GTM decision: paid social didn't work36:02 — Contrarian view: you don't need a sales team as early as you think37:10 — Remote first: why AI works better with written context40:34 — Final advice: hire for the role in 18 months, not 3 years ago

🎙️ Taking Legal Tech to Market is hosted by Paul Church, LegalTech recruiter, talent advisor, and one of the most listened-to voices in the space.

Subscribe for new episodes every week.

80-90% of your legal bill is overhead. AI makes it free. Nick Holzherr spent millions building and selling businesses, and most of it went on legal fees. That experience didn't just give him a product idea. It gave him a view of the law firm business model that most people inside it can't see.

In this trailer: the pyramid that makes law firm pricing impossible to reform, the wrapper question every LegalTech founder is quietly terrified of, and why a lot of the middle is going to run out of business.

Full episode live tomorrow. 🎙️ Taking Legal Tech to Market.

Half of every lawyer's day disappears into email. Not client work. Not billable hours. Email. And if a client doesn't hear back within 24 hours, that's already a signal of low customer satisfaction.

Sujith Jose saw this from the outside. He's not a lawyer, his only experience with legal was his own immigration process. But that distance gave him a view of a problem the industry had normalized into invisibility. So he built Candle AI: an email assistant built specifically for law firms that saves lawyers up to 90 minutes a day.

In this episode Sujith walks through the full GTM story, from a single conference pitch that became their first design partners, to why Meta ads outperformed LinkedIn and AI SDRs, to how one show generated over 50% of all leads for three months. He talks about pricing mistakes, the 90% trial-to-conversion rate, what purchase blockers taught him about product roadmap, and why the agentic adoption timeline in legal has compressed from two years to six months.

One of the most honest accounts of early-stage LegalTech GTM you'll hear in 2026.

Timestamps:00:00 — Introduction00:58 — What Candle AI does and who it's for01:31 — The 24-hour email rule and why it defines client satisfaction02:00 — Half a lawyer's day on email — the ABA statistic02:00 — The scaling trap: high touch service vs operational cost03:52 — Building in legal as a technical outsider05:50 — How a conference pitch became the product idea07:17 — First six months: design partners before sales08:51 — Expanding beyond immigration into all practice areas11:43 — Channel experimentation: LinkedIn, cold email, AI SDRs, Meta ads13:33 — One conference generating 50%+ of leads for three months13:33 — Partnership strategy with case management systems16:22 — The pricing mistake that cost them their closest advisor19:03 — VC backed vs bootstrapped pricing strategy20:35 — How purchase blockers became the product roadmap20:35 — 33% daily stickiness and 60–90 minutes average daily usage24:26 — AI adoption shift: law firms in 2024 vs now24:26 — Agentic workflows: two years compressed to six months26:11 — One month average sales cycle and 90% trial conversion27:44 — Hiring for agency, ownership, and AI leverage29:27 — Why everyone in a startup needs to be able to sell31:21 — What product market fit looks like from the inside31:21 — Next 12 months: marketing, inside sales, customer success hires

🎙️ Taking Legal Tech to Market is hosted by Paul Church, LegalTech recruiter, talent advisor, and one of the most listened-to voices in the space.

Subscribe for new episodes every week.

Half of every lawyer's day disappears into email. If a client doesn't hear back within 24 hours, that's already a signal of failure. Sujith Jose saw this problem from the outside, and built Candle AI to fix it.

Two months after his baby was born. One part-time engineer. A product that had to work fast.

This is the trailer for the full episode of Taking LegalTech to Market, covering the GTM reality of building in legal without a legal background, what early-stage selling actually looks like, and why the hints of product market fit are finally showing up in the metrics.

Full episode dropping tomorrow. 🎙️

Alex has spent 300 hours interviewing 200 LegalTech founders to produce one report. What came out of it wasn't a playbook, it was a diagnosis. Most founders build something they find intellectually interesting, then discover too late that nobody is willing to pay for it. The ones who survive figure out one thing first: are you giving the buyer an undeniable reason to change?

In this episode, Alex breaks down the three stages every LegalTech company goes through, pre-revenue, first clients, and one to five million ARR, and the specific go-to-market mistake that kills companies at each one. He talks about why two successful pilots is not product market fit, why the nine to twelve month post-raise window is the most dangerous period any founder will face, and why adding headcount before you've proven repeatability is building on shaky foundations.

He also calls out what's happening right now with vibe coding, the ability to build a prototype in an afternoon has made the validation problem worse, not better, because founders are moving even faster toward a market they haven't tested.

If you work in LegalTech, sell into it, build for it, or recruit for it, this is the most commercially honest 35 minutes you'll spend this week.

Timestamps:00:00 — The 9–12 month post-raise danger zone01:37 — What an undeniable reason to change actually looks like05:03 — First 90 days for a pre-seed founder08:41 — The vibe coding PMF problem11:47 — The two warning signals founders ignore17:15 — Geography and pricing mistakes in new markets21:21 — Why shaky foundations kill scaling teams23:45 — Pricing through the lens of the buyer26:17 — The spam cannon problem: 5,000 companies, one inbox30:23 — Where the LegalTech market is going next

Taking LegalTech to Market is hosted by Paul Church LegalTech recruiter, talent advisor, and founder of Talent and Growth.

🎙️ Subscribe for new episodes every week.

There are more than 5,000 LegalTech companies in the market right now. Most of them are blasting out cold emails, building products founders find interesting, and adding headcount on top of shaky foundations.

In this trailer, Alex gets honest about why most LegalTech GTM fails before it starts, and what the companies that actually win are doing differently.

New episode of Taking LegalTech To Market dropping on Friday. 🎙️

Andrew Ferguson joined Wordsmith as one of the first GTM hires. No sales function. No playbook. Founders undercharging by a factor of 20.

In this episode, Andrew breaks down how he built the go-to-market motion from scratch, segmented the team as the business scaled, and why the AI outbound wave didn't make sales easier, it made everyone start again.

He also gets honest about where salespeople are getting AI completely wrong, why quality still beats volume every single time, and what it actually looks like to sell legal AI into enterprise when GCs are still figuring out what they can trust.

If you're building a GTM team at an early stage LegalTech company or trying to figure out how to use AI in your sales motion without becoming just another piece of inbox noise, this one's for you.

🎙️ Taking LegalTech To Market with Andrew Ferguson, Head of Sales at Wordsmith.

Chapters:

00:02 - Walking into a 9-person startup with no sales function and an underpriced product02:47 - Building the car while driving it, what a normal week looked like early on05:26 - How AI has completely changed the discovery process07:35 - Where salespeople are getting AI wrong and why it ends up with poor execution09:30 - The AI outbound wave that flooded every inbox and devalued everything12:43 - Getting back to Wordsmith, how rapid growth led to team segmentation13:30 - How the enterprise, mid-market and SMB teams were carved out15:55 - Proving the motion is repeatable across multiple people, not just three18:00 - What selling legal AI into enterprise actually looks like today22:00 - What GCs really want before they trust AI with high value contracts26:00 - What's next for Wordsmith in the next 12 months

The AI outbound wave crashed. Inboxes flooded. Response rates collapsed. And yet most sales teams are still running the same motion. Andrew Ferguson walked into Wordsmith when there was no sales function, no playbook, and a product being undercharged by a factor of 20. What he built in the first year, across three market segments, through a 10x growth period, and into a US expansion, is the most honest account of what early-stage LegalTech selling actually looks like. No inspiration. No platitudes. Just what worked, what didn't, and where the market is going next.