The Soft-Landing Buyer Playbook: Runway Date to a Ranked Acquirer Slate

When a portfolio company has a cash-out date it can't raise past, someone on the investor side has to work out who would buy the team, the technology or the customers, and reach those buyers while there is still time to close. This playbook is for the board member, platform partner or angel who owns that job. In about a week it turns one company and its cash-out date into a ranked slate of 15 to 25 likely acquirers. Each row has a buyer thesis, dated evidence of appetite, a named product leader and corp dev contact, the strongest warm path from the fund's network, and a latest-start date worked back from the runway.

When is a soft landing still possible?

A soft landing is realistic if you start with roughly 5 to 6 months of runway. With less, notice law and normal deal timing leave almost no room to close. That floor is worked out from practitioner guidance, not from a published deal sample, so treat it as a planning number and not a rule.

Four terms used throughout:

• Soft landing: any exit that places the team with a buyer instead of ending in a shutdown and layoffs.
• Acquihire: a deal where the buyer pays mainly for the people. The entity price is usually small and most of the value sits in retention grants.
• Licence-and-hire: a structure where the buyer licenses the technology non-exclusively and hires the staff, without buying the company's shares or assets.
• Slate: the ranked list of candidate buyers that this playbook produces, one row per buyer.

No one has published a sample of acquihires with timings. Everything known comes from guides and founder accounts, and they roughly agree:

An LOI (letter of intent) is the signed summary of terms that comes before the definitive documents. The same Hacker News thread has a blunter data point: 1.5 months is likely not enough to close. The advised start points differ. SunsetHQ says about 6 months, and Startupfundraising.com calls 6 to 9 months ideal. If your company is already below the floor, still run the playbook, but squeeze steps 2 to 5 into as few days as you can and plan the fallback seriously from day one.

The cash-out date also hides a second cost: the company keeps existing after the deal closes. Kruze Consulting advises waiting three to six months after closing for payments to settle before winding down. So the company needs enough cash left to stay open through that tail, and the close itself cannot be timed for the last day of cash.

How do you work the clock back from the cash-out date?

The date that drives everything is the layoff-notice deadline, not the cash-out date. Depending on headcount and state, it falls 60 or 90 days before cash-out, and a signed LOI must exist by then or notice goes out.

WARN (Worker Adjustment and Retraining Notification) laws require advance notice before closures and mass layoffs. Which rules apply depends on where the staff work and how many there are:

• Federal WARN: covers employers with 100 or more full-time employees. It requires 60 days' notice before a plant closing (50 or more workers at one site) or a mass layoff.
• California (Cal-WARN): starts at 75 employees, counts part-time staff, and is triggered by a layoff of 50 regardless of what share of the workforce that is.
• New York: starts at 50 full-time employees, requires 90 days, and covers cuts of 25 or more at one site.
• Nebraska, New Jersey, New York and Maine: all require 90 days. New Jersey and Maine also add statutory severance.
• Everywhere else: sixteen states have their own layoff-notice duty, so check every state where the company has staff, not only its headquarters.

State rules differ and get amended, so counsel signs off the calendar. Your job is to make sure counsel has the right inputs: headcount by state, full-time and part-time counted separately, and the cash-out date.

A worked example: 60 people in New York

The company is too small for federal WARN, which starts at 100, but it is covered by New York's law, which starts at 50 full-time employees. Notice is 90 days. Counting back:

• Notice deadline and latest LOI date: 90 days, or about 13 weeks, before cash-out.
• Latest first contact with buyers: about 3 weeks earlier, so roughly 16 weeks before cash-out.
• Latest kickoff of this playbook: about a week earlier again, so roughly 17 weeks before cash-out.

The close then fits into the 4 to 12 weeks after the LOI, inside the notice period. But 17 weeks assumes the first wave of buyers works and every step takes the fastest published time. Add room for one failed wave and a slow close, and kickoff moves to 5 to 6 months out. That matches SunsetHQ's advice to start at about 6 months.

The playbook, step by step

The playbook has eight steps. The first five build the slate in about five and a half to seven and a half working days of platform-team time. The last three run the deal against the clock.

Owners matter, because each step stalls when nobody owns it. The board member owns step 1. The founder and platform partner own step 2. The platform or talent partner owns steps 3 to 5. The founder runs step 6 with intros from the fund.

One question the sources leave open is whether to tell staff first. One founder account on Hacker News says to tell the team now and let them job-hunt full time. Another describes a founder who tested acquirer interest before telling the team. My position is narrower than either. You cannot pre-clear acceptance without talking to the key employees, so they have to know before step 6. When to tell everyone else is a call for the founder and counsel.

Where do candidate buyers come from?

Candidate buyers come from four public signals that can each be seen and dated: adjacency, matching open roles, prior acquihire or licence-and-hire history, and recent hires out of the company. None of them has been tested as a predictor of appetite. Each one tells you who to talk to, not who will buy.

Before collecting any signals, write down what the buyer would be paying for. Every row on the slate gets one primary thesis:

• Team: the buyer needs these engineers, and the code is secondary.
• Tech: the buyer wants the product, the code or the IP.
• Customers: the buyer wants the customer book or the distribution.

The thesis decides who you approach and what the price conversation looks like, so a row without a thesis is not finished.

Open roles: check the date and the person

A matching job posting is the most current signal and the easiest to fake. A posting only counts if it was posted within the last 60 days and the hiring manager can be found as a real person at the company. If no such person exists, the posting is a recruiting placeholder and tells you nothing about appetite.

Recent hires: the signal that cuts both ways

A buyer that has recently hired engineers away from the portfolio company has shown it values them. It has also made the remaining team worth less. Daniel Kim's research on startup acquisitions finds that departures before an acquisition strongly predict departures after it. A buyer that knows this will price in the risk. So for every leaver, check whether they were a key employee. If the buyer has already taken the people on your must-accept list, move the row down.

Tracing leavers is the slowest part of the universe build when done by hand, because each person has to be matched to a current employer and a start date. Refolk handles this as a plain-English request for the company's former engineers and where they work now, which gives you the poaching signal and the list of buyers in one pass.

A retention tiebreaker

Research summarised by MIT Sloan finds that acquirers holding patents lose fewer acquired employees. That says nothing about appetite, but between two otherwise equal rows it is a reasonable tiebreaker, because retention is what the buyer is pricing.

How do you score and rank the slate?

Score every candidate on three things: thesis fit, strength of evidence and warm path. Flag regulatory structure separately, then cut to the top 15 to 25 rows. The score decides who goes into the first wave of three or four. The flag tells the board what kind of scrutiny the deal might attract after it closes.

The rubric below is my method, not a published standard. The weights are deliberately even, because no study has shown that any one signal predicts appetite better than the others.

Rank | Buyer | Thesis (team / tech / customers) | Evidence (signal, date, source) | Product leader | Corp dev contact | Warm path (connector, relationship) | Reg flag | Latest start date | Score

THESIS FIT (0 to 3)
0 = no clear reason to buy
1 = adjacent only
2 = one clear thesis with a named owner inside the buyer
3 = clear thesis that matches the skills matrix and the must-accept list

EVIDENCE (0 to 3)
0 = none, or undated
1 = one dated signal older than 60 days
2 = one dated signal within 60 days
3 = two or more dated signals, including a prior acquihire or licence-and-hire

WARM PATH (0 to 3)
0 = cold
1 = second-degree through someone outside the fund
2 = a fund partner or portfolio founder who knows the entry person
3 = a fund partner or portfolio founder who has done a deal with the entry person

REG FLAG (no score)
Mark Y if the likely structure is licence-and-hire with one of the largest tech platforms.

What the regulatory flag means

HSR is the US Hart-Scott-Rodino premerger notification regime: deals above set thresholds must be filed with the antitrust agencies before closing. The FTC adjusts the thresholds every year. At the last adjustment the minimum size of transaction was $133.9M, and deals above $535.5M were reportable whatever the size of the parties, unless exempt. A filing starts a 30-day initial waiting period. Check the current figures on the FTC's thresholds page before you rely on them.

Classic acquihires fall well below these thresholds. Licence-and-hire structures avoid HSR because the Act requires an acquisition of assets or voting securities. The regulators have shown they can still act after the fact:

• The UK's CMA found that Microsoft's hiring of Inflection staff, a deal of about $650M, was a relevant merger situation, and then cleared it.
• Google paid $2.7B for a non-exclusive licence to Character.AI's technology. The DOJ opened an investigation after the deal had closed.
• The FTC chair has said the agency will review whether acquihires are structured to escape HSR review. Senators Warren, Wyden and Blumenthal have written to the FTC and DOJ about the same practice.

The sources report no enforcement action so far, so check before you rely on that. For the slate, the practical point is that the flag means possible scrutiny after close. It does not move the close date and should not lower a buyer's rank on timing grounds.

How do you find corp dev contacts at acquiring companies?

Every row needs two names. One is a product or engineering leader who owns the talent need. The other is a corp dev person who owns the question of company value. The corp dev pool is small and concentrated, so for a team-thesis buyer the product leader is often the better way in.

The distinction matters in the first meeting. A product leader is solving a hiring problem and thinks in engineers and months saved. Corp dev is pricing a company and thinks in entity value and risk. Know which conversation you are walking into before the intro goes out.

All figures come from Refolk's index. Read them with three caveats:

• The region shares come from 25-person samples. They show direction, not precise shares.
• The counts cover the plain title only. Searches that combined title variants with industry filters returned zero results, so there is no breakdown by seniority or segment, and people with variant titles are not in these numbers.
• The title does not tell you the segment. In the US sample, the most common employer was Amazon (3), followed by DoorDash, Anthropic, NetApp, Webflow, Zeta Global and Netflix with one each. In the UK sample it was Google (2), followed by ElevenLabs, Yubico, ITRS and myPOS. Many UK holders of the title also work at non-tech firms such as Rothesay and PwC.

For a UK portfolio company the gap matters. A US buyer's corp dev team is probably not in London, and the UK pool is concentrated there. In that case, start with the product leader at the buyer's local engineering site and bring corp dev in once there is a thesis on the table.

Picking the warm path

For each row, list every route from the fund to the two named people, then keep the strongest. In order: a partner or portfolio founder who has done a deal with the entry person, then one who simply knows them, then a second-degree link outside the fund, then a cold approach. Searching the fund's network against each buyer one at a time is where this step loses its two days. Refolk can run the whole thing as one request, for example the heads of product at a set of named buyers who are connected to the fund's partners. That returns the people and the connecting partner together.

Subject: Quick intro ask: [Buyer] and [Portfolio company]

Hi [Connector],

I'm on the board of [Portfolio company]. The team is [N] engineers strong in [two or three core skills], and we're exploring a strategic home for them before [notice deadline].

[Buyer] looks like a fit because [one line of dated evidence: open role posted on date, or prior deal on date].

Would you be willing to introduce [Founder] to [Product leader name], who runs [team or product area]? A short forwardable note is below.

Timeline is real: we need serious conversations under way within three weeks.

Thanks,
[Name]

--- Forwardable ---
[Founder] leads [Portfolio company], a team of [N] engineers working on [one line]. They are exploring a strategic combination with a short timeline and think [Buyer]'s [team or product area] could be a strong fit. Open to a 30-minute call?

What buyers pay, and which part reaches the fund

Published per-engineer prices differ by about 10x because they measure different pools of money. Investors are paid only from the entity price, so the fund should negotiate the entity floor, not the headline number.

In a16z's worked example, $200,000 is paid to the company for each engineer who accepts an offer, capped at $2M. The other ranges add retention, which goes to the engineers and not to the cap table. Cash to investors is often just enough to return the preference stack. Most of the value goes into RSUs that vest over 2 to 4 years. WaveUp's example shows what that means: a $1M entity price against $2M raised on a 1x non-participating preference leaves investors with a 50% loss.

Buyers structure deals this way because acquired staff leave.

Over a three-year window, acquired workers are about 15% more likely to leave. Retention grants that vest over time hedge that risk for the buyer. That shrinks the entity price, and with it how much of the preference the fund recovers.

Acceptance conditions

Most LOIs make the deal conditional on enough people accepting their offers. Two forms are described:

• Key-employee condition: a16z suggests requiring 100% of key employees to accept post-closing offers.
• Headcount threshold: Will Larson describes a threshold such as eight of ten engineers signing.

No one has published how often each form is used. On the seller side, a headcount threshold is less fragile. If the buyer insists on 100% of key employees, step 6's pre-clear stops being optional.

How does this go wrong?

Most failures come from treating a signal as proof, or from comparing two numbers that measure different things. Each failure below has a check you can run before the row reaches the first wave.

1. The clock is set from the wrong date. Using the runway date as the deadline when New York or New Jersey notice moves it 90 days earlier. Check: count headcount by state, and include part-time staff wherever Cal-WARN could apply.
2. Prices are compared across pools. Treating a16z's $200K and a $1M to $3M range as if they measured the same thing. One is entity cash and the other is the total including retention. Check: label every figure with its pool before anyone repeats it in a board update.
3. A stale posting reads as appetite. Evergreen or old job postings look like live demand. Check: the posting date is within 60 days, and the hiring manager exists as a named person.
4. Poaching is read as pure appetite. A buyer that has hired from the company may already have taken the people it wanted, and departures before a deal predict departures after it. Check: compare the leavers against the must-accept list, and move the row down if they overlap.
5. The corp dev contact is in the wrong segment. In Refolk's index, many UK holders of the title sit at non-tech firms such as Rothesay and PwC. Check: confirm the person holds the title at a buyer in the right segment, not at an adviser.
6. HSR is treated as a delay risk. Classic acquihires fall below $133.9M, and the DOJ's Character.AI review began after closing. Check: describe the flag to the board as possible scrutiny after close, not as a later close date.
7. The acceptance condition fails on one person. A 100% key-employee condition collapses if one engineer is already interviewing elsewhere. Check: pre-clear acceptance with each key employee, privately, before any LOI.

The most expensive of the seven is the first one, because it is the only one you cannot fix later. Every other failure costs a row or a week. A wrong clock costs the whole exit.

The runway date is not your deadline. The notice date is, and it can arrive 90 days earlier.

How do you keep the slate current?

A slate is only as good as its newest date. During outreach, re-date the evidence on the top rows every week. Between companies, keep the template and the rubric, so the next stalled company starts at step 1 instead of from nothing.

While the deal is live:

• Weekly: re-check the posting dates on the open-role signals for the top 10 rows and drop any that have gone stale.
• Weekly: re-run the leaver search on the portfolio company. Every new departure changes both the poaching signal and the must-accept list.
• At each wave: if the first three or four buyers have not produced an LOI path within about three weeks, take the next three or four from the top-right quadrant and send intros the same day.

Across the portfolio:

• Every year: re-check the HSR thresholds on the FTC's page, and have counsel confirm any changes to the state notice laws that affect your companies.
• For each stalling company: start this playbook when runway reaches about 6 months, not when the next round has visibly failed. By then the clock has usually already been decided.