Chris Hamm (former evaluator) and Kyle Peterson (contracts manager turned Customer Success leader) break down how bids and contracts work is evolving—especially around compliance, clause reviews, and the surge in proposal volume. They also explore where AI helps (briefs, alignment, drafting) and where it raises new risk (NDAs, data controls, model “learning”)
What’s really changing in the GovCon bid and contracts landscape—and what does that mean for the people doing the work? In this episode, host Chris Hamm brings the evaluator viewpoint (1,000+ proposals reviewed across written evaluations, orals, demos, and source selections) into a practical conversation with Kyle Peterson, a former aerospace contracts manager who now leads Customer Success at VisibleThread.
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They walk through the “real day job” friction: parsing Section I clause lists and flowdowns, catching security and classification requirements that don’t belong, building compliance matrices, and comparing multiple RFP amendments—work that can quietly consume entire days. Kyle shares concrete time-savings examples (hours → minutes) and why those gains aren’t just productivity—they’re also risk mitigation.
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The second half shifts to AI: how GenAI can support briefings, alignment to prior work, and early drafting—paired with deterministic methods that show exactly where requirements appear in the document. They also address the new wave of NDAs and customer clauses that restrict proprietary data from being ingested into learning/training models, plus the questions every GovCon team should ask about data handling and controls before adopting AI-enabled tools.
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00:02 — Intro + why this episode is different (VisibleThread-focused; Chris “plays the novice”)
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00:43 — Kyle’s background: aerospace contracts manager → Customer Success leader
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02:17–03:38 — Clause/flowdown reviews: “two screens,” hours of cross-referencing, and the real pain point
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06:51–09:25 — How teams start: upload docs + persona-based workflows; SAM.gov integration and lifecycle view
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12:19–14:45 — GenAI vs deterministic: briefings, alignment, and “show me where it is in the doc”
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16:30–17:52 — Writing + audience: translating technical content for audits (DCAA) and building trust
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18:30–19:25 — Time savings examples: “shall” extraction (hours → minutes) + amendment comparisons (8 hours saved)
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19:51–20:40 — Who buys tools like this (and the “VisibleThread alumni base” effect)
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22:09–27:48 — Market shifts: non-traditionals, OTAs/CSOs realities, and why tools can’t rely on a single data source
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33:06–35:43 — NDAs + AI: “you shall not” clauses, model learning, and what to ask vendors
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38:56–41:24 — Evaluator perspective: why tools fell out of evaluation, and why AI is coming back to speed awards
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