Advertise on podcast: Reps & Remedies: A Practical Primer for M&A Deal Lawyers

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A $300 million AI target can turn into a paperweight if the model was trained on data the company never had the right to use. This deep dive gives deal lawyers a spotting-and-routing framework for AI risk across three postures: buying an AI company, buying a business that uses third-party AI, and buying a vendor or contractor selling or operating AI workflows for customers. The discussion covers training-data provenance, ownership of models, weights, outputs, open-source dependencies, bias and compliance reps, interim covenants around deployment changes, the agentic-AI contract checklist for vendor and customer paper, downstream liability allocation, and the still-forming RWI response to known AI issues. It also maps when pricing, earnouts, retention, escrows, or structure may need to move. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. The clean closing myth dies fast once a live deal starts moving. This capstone episode walks through a $200 million healthcare-services acquisition from kickoff call to month-eight claim, showing how authority, structure, conflicts, LOI leverage, and diligence findings become drafting choices in the SPA. It covers how a pending regulatory inquiry and a related-party lease migrate into price, covenants, schedules, and a special indemnity; why the real negotiation fights sit in the working capital peg, materiality scrape, sandbagging, RWI, and earnout mechanics; and how HSR delay, ordinary-course covenants, MAE posturing, bringdown certificates, funds flow, and payoff-letter choreography decide whether the wires actually move. The episode closes by tracing a later enforcement action through baskets, caps, exclusions, and the fraud question. References to federal or state healthcare laws and regulations in this episode are illustrative and should not be treated as a complete or authoritative statement of current law. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. When a buyer wants out, sloppy case lore is expensive. This episode revisits the Delaware decisions that actually changed private M&A drafting and strips away the slogans lawyers repeat in markups. The discussion is a 101-level introduction to the caselaw of IBP v. Tyson on specific performance, Akorn on what an MAE record had to look like, AB Stable on ordinary-course covenants tied to past practice, and ABRY Partners on the line between extra-contractual anti-reliance and lies inside the reps. It then reviews Snow Phipps with nuance, focusing on financing-efforts obligations, prevention-doctrine pressure, and why reverse-termination-fee exclusivity depends on the remedies stack and breach theory. The episode closes by isolating the provisions that most often decide the fight: reliance architecture, ordinary-course language, specific-performance triggers, efforts covenants, and fee exclusivity. Please note that this episode was produced in April 2026 and is intended to be a basic overview of Delaware caselaw as it relates to certain M&A concepts. It is not a fulsome review nor should it be relied upon as an accurate representation of the facts or decisions of the cases referenced. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A $20 million headline bump can disappear the moment you trace the recourse. This episode puts a $420 million sponsor bid next to a $400 million strategic offer and asks what the board is really being paid for. The discussion breaks down debt commitment letters, highly confident letters, SunGard-style certain-funds mechanics, market flex, and the side-door financing risk hidden in marketing-period covenants. It then turns to the equity commitment cap, reverse termination fee sizing, and the conditional nature of specific performance in financed deals. The second half focuses on management rollover as a new investment with conflict, governance, drag-along and tag-along implications, plus why RWI often produces exclusions, special escrows, or both. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. $30 million of hidden IP exposure is where boilerplate stops being boilerplate. This episode stages a buyer-seller debate over a patent claim allegedly concealed by the seller's CEO and uses that fight to test the real boundary between extra-contractual fraud and lies embedded in the reps themselves. It works through FdG Logistics, ABRY Partners, and Prairie Capital, then turns to the drafting choices that decide who can actually be sued: fraud definitions, carveout scope, survival periods, exclusive-remedy language, and non-recourse provisions. The second half shifts to broken-deal remedies, including must-close, efforts-plus-fee, and hybrid models, plus specific performance, reverse termination fees, willful-breach language, and the sponsor guarantee chain. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A $3.5 million contract loss is where the promise of a clean exit starts to break down. This episode takes the undisclosed change-of-control termination-right claim from Episode 13 and runs it through the RWI layer, focusing on buy-side policy structure, the underwriting record, and the line between an unknown breach and a known issue. It covers no-known-loss and no-known-circumstances declarations, retention mechanics that may look very different from the SPA basket, notice and proof requirements, and the subrogation limits that usually matter most to sellers. The discussion also shows why policy wording, knowledge imputation, and fraud carveout alignment across the SPA and policy can decide whether insurance is real recourse or just optics. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. Eight months after closing, one unscheduled change-of-control clause turns a $4 million customer loss into a live test of whether the SPA's remedies architecture actually works. Using an undisclosed termination right in the target's largest customer contract, this episode treats indemnification as a negotiated recovery system rather than a boilerplate afterthought. It walks through notice timing and specificity, lane classification across rep breach, covenant breach, schedule deficiency, and fraud theories, the economics of a $500K tipping basket versus a true deductible, and the interaction of survival periods, caps, the definition of Losses, escrow collectability, sandbagging, exclusive-remedy clauses, and the RWI layer. The result is a practical claims map for lawyers who draft these provisions under signing pressure. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. At 1 a.m., six words in the MAE definition can move nine figures of sign-to-close risk. This episode is a technical markup drill on the private-company MAE clause itself, starting with the forward-looking prong, the aggregation language, and the buyer's attempt to build a mosaic while the seller tries to atomize the facts. It then works clause by clause through the carveouts for macro conditions, industry shifts, law and GAAP changes, pandemics, force-majeure-style events, war, announcement effects, and buyer-caused consequences, before turning to disproportionate-effects pullbacks, comparator fights, and the meaning of company and subsidiaries taken as a whole. The episode ends by tracing where the definition actually bites in MAE-qualified reps, bringdown conditions, standalone no-MAE closings, and interim-covenant disputes. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. Two weeks from the outside date, a 28% revenue drop can turn a signed SPA into trench warfare. This episode stages a live buyer-seller showdown over whether a $300 million private deal still has to close after customer losses, a new regulatory investigation, a CFO resignation, and a nervous lender. The discussion works through why MAE is a risk-allocation concept rather than shorthand for business disappointment, how Akorn and durational significance shape the analysis, and why bringdown wording, officer certificates, and ordinary-course compliance can matter more than headline deterioration. It also covers specific performance under IBP v. Tyson, reverse termination fees, financing failure, and the leverage created by waiver, cure, and outside-date mechanics. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A decision that saves the business can still hand the buyer a closing weapon. This episode treats the ordinary-course covenant as the interim governance charter for a company with two masters, then runs three live-fire scenarios through the text: a 15% concession for a 22%-of-revenue customer, $800,000 in retention bonuses blocked by a no-increase-in-compensation covenant, and $1.2 million of emergency repairs against a $500,000 capex limit. The discussion tracks AB Stable’s pressure on "consistent with past practice," why consent mechanics and response timing are substance rather than process, how efforts standards allocate execution burden, and why operating matrices, gun-jumping discipline, and emergency carveouts now sit at the center of interim-covenant drafting. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A bracketed scrape clause can decide whether a six-figure problem ever reaches the indemnity ledger. This debate episode tests full-scrape and selective-scrape positions against the rest of the SPA architecture rather than treating the clause in isolation. The discussion works through breach versus loss-calculation scrapes, deductible versus tipping baskets, the double-materiality trap created by rep text and schedule filtering, and the sandbagging collision when a buyer knew about the issue before closing. It also covers mini-baskets, subject-defining materiality in reps like material contracts, and why RWI underwriters may see a full scrape as either cleaner claims mechanics or added operational noise. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. At 2 a.m., a vague schedule entry can erase the protection a heavily negotiated rep was supposed to deliver. This episode treats disclosure schedules as the deal’s routing layer: the mechanism that decides whether a fact actually qualifies a rep, forces a rewrite, supports a special indemnity, or should change price. Using a late-night schedule review triage, the conversation walks through unusable material-contract and litigation entries, why "see data room folder 4.3.2" usually is not contractual disclosure, how contradictory scheduled facts must be analyzed against the rep text and disclosure legend, and why portability, fair-disclosure standards, double materiality, and post-signing supplements reshape buyer leverage and RWI outcomes. It also flags AI contract schedules as a growing drafting pressure point. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A single qualifier can turn a core rep into a cosmetic promise. This episode examines which SPA representations actually drive claims and leverage in private M&A, and why the loudest markup fights often miss the real risk. The conversation breaks down statement architecture through scope, qualifiers, timing, and remedial consequence; the distinction between fundamental and general reps in setting survival, caps, and baskets; how materiality, MAE, and knowledge qualifiers reprice what the seller is actually promising; and why sandbagging, schedule design, bringdown mechanics, and late schedule updates determine whether a rep works at signing, at closing, or only on paper. It also covers overlooked interim-operating, full-disclosure, buyer, and emerging AI-specific reps. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A $15 million earnout can evaporate even when the product is performing. This episode examines how contingent consideration shifts risk after closing in a founder sale of a cybersecurity SaaS company to a PE buyer planning immediate integration. The conversation breaks the earnout into four bargains — price, operating behavior, measurement, and payment security — and shows how metric choice between ARR, revenue, EBITDA, and bookings creates different manipulation risks. It also covers bundling and attribution rules, dedicated-sales-team and anti-diversion covenants, the Delaware implied-covenant backdrop for earnout fights, accounting hierarchy and deferred-revenue distortions, change-of-control acceleration, credit support, and the point at which an earnout is so synthetic that rollover equity, retention arrangements, or no earnout may be the cleaner answer. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.

This podcast uses AI-assisted writing and AI-generated audio; see the production note below and at www.repsandremedies.com. A $4 million swing can sit inside a single working-capital definition. This episode examines how a closing-accounts true-up becomes a negotiation over price, seasonality, and post-closing leverage in a $150 million deal for a seasonal distribution business. The conversation pits a trailing-twelve-month peg against a last-month-end peg, then digs into the accounting hierarchy among GAAP, past practice, deal-specific methodologies, and the sample balance sheet that makes commercial intent executable. It also covers the consistency-versus-correctness trap, collars and de minimis thresholds, buyer control of the closing statement, true-up payment security when the escrow is short, and why customer advances, banker fees, and covenant claims do not all belong in the same dispute lane. Production disclosure: This podcast is for informational and educational purposes only. It is not legal advice, does not create an attorney-client relationship, and is not a substitute for advice from counsel licensed in your jurisdiction. Law and deal practice change, and information may become outdated. No confidential client, deal, or matter information is discussed. The views expressed are the author’s alone and do not reflect the views of the author’s firm or its clients. This podcast includes AI-assisted writing and AI-generated audio. The underlying instructional modules were developed with substantial assistance from OpenAI GPT-5.4, reviewed and refined with input from Anthropic Claude Opus 4.6, and further synthesized into audio by Google NotebookLM. Final topic selection, source curation, and editorial judgment remain with the creator. Some episodes may retain occasional stylistic or tonal artifacts from AI-assisted production.