Sam Woods

Every AI tool you evaluate right now will get replaced or shut down within ~12 months. The durable asset is your own operating file: how you qualify a lead, and the exact rules for when a pipeline deal is dead. Rented wrappers leave your margin exposed.

Hard boundary in my competitor watch agent: never let it recommend pricing. The agent inspects public marketing copy. It has zero visibility into internal unit economics or gross margins. Optimizing against a competitor's public tier quietly burns your own gross margin.

Audited an agency doing roughly $1.2M that wanted to automate lead intake: The founder assumed deploying a qualification agent was about scoring intent. The audit showed something else: We pulled the first email and form submission across ~50 won deals and checked the exact friction point prospects brought up before booking: - Was there a technical integration question? - Were they checking support for their specific CMS? - Were they trying to figure out if pricing fit their budget tier? The top 3 friction points showed up in ~30 of those 50 deals. We fed those three points straight into the intake agent as structured qualification gates before anyone gets on the calendar. When an agent qualifies against real historical friction instead of generic intent, pipeline qualification goes from guessing to math.

Open your client list and write next to each name the date you last offered them something new or asked them for an introduction. I'd bet the client you'd most like an introduction from has never been asked. Tell me if I'm wrong.

Audited a ~$3.2M B2B agency that let an automated qualification agent write directly to their CRM: Within 72 hours, it had marked 19 unresponsive accounts as closed-lost and emailed a discount offer to a client who had renewed the day before. When an automation fails, you usually get a red error alert in your dashboard. When an agent hallucinates, it keeps running with complete confidence, silently modifying records and talking to buyers behind your back. The owner pulled it off live accounts and put it on a three-stage leash: > Stage 1: Read-only shadow mode for two weeks > Stage 2: Draft mode (outputs queue for 1-click human review) > Stage 3: Live execution with strict negative constraints If an agent doesn't earn production trust on training wheels, you don't give it write access to paying customers.

An agent that finds something on every single run is just promoting noise to stay interesting. When briefing agents are forced to deliver daily updates, they pad themselves to fill space. Give them explicit permission to return empty reports, or you drown in alert fatigue.

The easiest way to build new service offers is mining past declined proposals where manual labor was too expensive to deliver profitably. Rebuilding those dead scopes with automated pipelines turns them into offers running at roughly 80%+ gross margin.

If there's no quote or event behind it, the signal scores zero. That's the first rule I'd give any AI that scores your clients, because left to itself it counts politeness as praise and small talk as a buying signal. The four lines I'd paste into its instructions: 1. Praise counts only when the client starts the message or raises it unasked. A thank-you in reply to my email scores zero. 2. A new need is a problem the client named in their own words. A general comment about being busy, growing or hiring scores zero unless they connected it to something I sell. 3. Momentum is a change against this client's own pattern in the previous 90 days. A client who has always written often has not moved. 4. Never score my own activity or anything inferred about the client. The full agent, with the scoring prompt and the monthly board: bionicbusiness.com/p/run-cus…

One builder's quality check on AI-made videos cost $127 a video. With cheap automatic checks in front and only the flagged defects sent to the expensive model, the same check cost $0.16. Those are his own figures. On Monday, existing Notion customers move to the new AI credits. Their agents can now work on one task for 24 hours, and nobody knows yet what one of those runs will cost. So give an agent one job you can check in five minutes, run it once, and read what it cost. That number tells you how much of your backlog to hand it.

Audited a ~$180k solo consulting practice with ~6 retainers: The problem wasn't client delivery. The audit showed something else: - ~53 of ~69 monthly ops hours burned - ~11 tabs open just coordinating updates C'mon man.

Agency founders will raise prices 20%, then give every dollar back in unpaid Slack messages and unbilled revision rounds. Clients always assume whatever isn't explicitly ruled out is included. Raising rates does nothing if your boundaries are porous. I started adding explicit "what we do NOT do" sections directly to proposal templates so expectations are locked in before kickoff. Protects margin better than any rate hike.

A SaaS founder I advise doing ~$20M ARR fired his entire SDR team for an autonomous inbound system. About 6 weeks later, he called me in a panic because his pipeline was breaking. He had fired the human team to cut CAC. The data showed what actually happened: - Inbound volume jumped roughly 4x - Calendars filled with unqualified clicks - AE win rates collapsed by about 60% - The entire pipeline collapsed When an agent floods calendars with unvetted leads, your most expensive reps spend roughly half their week babysitting bad calls instead of closing margin. Automating top of funnel without mapping unwritten qualification rules just burns sales capacity.

The mistake isn't hiring an agent to run a workflow. It's hiring an agent to run a workflow before you've written down how a human does it well. You can't encode judgment you haven't examined. Most agentic builds skip this step entirely. They wire up the tools, set the trigger, and watch it run. Then wonder why the outputs are technically correct and operationally useless. The debugging loop that follows costs three times what the build did. Write the manual version out first. Every decision point. Every filter. Every condition where a human would pause and check something. That document is your actual architecture. The code is just a translation of it.

A client who loves working with you can still be the wrong person to offer your next program to. A second purchase needs a second problem to solve, so the buy-more score looks for three things: - a result they'd name - engagement rising against their own normal - a new problem they've raised in their own words For a referral, swap the new problem for praise they gave without being asked. A referral puts their name next to yours, so they have to be pleased enough to vouch for you. Both readings need the result. A client who hasn't had anything from you yet won't buy more or send you a friend, however much they like you.

If you run agents in your sales or ops pipeline, give each one an operational boundary contract. It's one markdown file that lives in the agent's context, six lines per workflow: - Trigger: the exact event that wakes the agent up. - Input: what it is allowed to read (and what it cannot touch). - Action: the single discrete change it makes. - Gate: the validation rule it must pass before writing data. - Fallback: where it routes when confidence drops below 90%. - Log: the one-line summary it posts to Slack. Then add one standing constraint to the system prompt: "If an action requires guessing outside these six boundaries, stop execution and notify an operator." Most broken automations happen because teams hand an agent a goal instead of a fenced lane.

Defaulting every background task to frontier models is a quiet margin killer. We found roughly $2,600 a month vanishing across ~50,000 routine calls. Jesus take the wheel.

When I ask consultants and coaches how they decide which client hears about their next offer, the honest answer is nearly always whoever they spoke to last. The clients who are ready have usually said so already. One asks on a call whether you also work with their team. Another emails, without being asked, to say what changed for them since they started. None of it turns into a conversation, because the month fills up and nobody reads it back. So I'd hand that reading to an agent. Once a month it goes through every client's last ninety days of call notes, email and payments, and scores four signals, each with a dated quote or event behind it: - a result they'd name - engagement rising against their own normal - a new problem you could solve - praise nobody asked for Then it reads the score two ways, once for who's ready to buy more and once for who's ready to refer you. It holds back anyone with something open or anyone you asked recently, and cuts the list at the number of conversations you have room for this month. It never contacts a client or names a price, and for each client who makes the cut it writes you an opening question built from something they said. The first version takes about forty minutes: one sheet of clients, ninety days of notes, and one prompt in the AI you already pay for.

An agency owner I work with lost a ~$4,000/mo retainer to an onboarding delay: > Closed the deal > Welcome email delayed > Kickoff pushed > Client rescheduled > Internal prep meetings stacked up > First deliverable landed roughly 19 days in The client spent those 19 days wondering if they made a mistake. Delivering automated audit notes within about 90 minutes of payment flips the dynamic immediately. The client holds something tangible on day one before anyone even joins a kickoff call. Painful.