Theodore Cochran

FibrX https://www.fibrx.io/ Strategic Importance of U.S. Shipbuilding The U.S. is hearing renewed calls to bring shipbuilding back to American shores. Recent announcements from the Trump Administration highlight plans for a new “Trump-class” of battleships, massive 30,000–40,000 ton vessels envisioned as the largest surface combatants since World War II (USNI News, Dec 22, 2025). For decades, America’s share of global shipbuilding fell to just 0.1% (1), while China now commands more than 53.8% (2). China’s shipyards don’t just build commercial vessels for foreign buyers. They also produce warships for the People’s Liberation Army Navy (PLAN). This dual‑use model has helped China grow the PLAN into the largest navy in the world, with more than 370 ships today and projected to reach 435 by 2030 (3). The U.S. response is the “Golden Fleet” initiative, tying naval expansion directly to economic revitalization. Billions in defense appropriations have already been allocated. The FY2025 defense budget totals about $841 billion (4), with shipbuilding projected to average $40 billion annually over the next 30 years (5). The Significance - National Security: A modern fleet is essential to counter peer competitors. - Industrial Base: Shipbuilding strengthens supply chains, skilled labor, and advanced manufacturing throughout most industries. - Innovation: New warships will integrate AI, hypersonic weapons, advanced sensing systems, and directed energy capabilities such as high‑energy lasers and electromagnetic pulse weapons. The FibrX Interface At FibrX, we see a transformational role for our technology in this naval renaissance: - Detecting corrosion early to reduce lifecycle costs. - Embedding light weight, low profile fiber optic sensors for real‑time structural intelligence. - Enabling uncertainty-aware analytics enhanced digital twin models for predictive maintenance. - Aligning with “Buy American” priorities by strengthening domestic supply chains. Closing Thought The strategic importance of U.S. shipbuilding lies not only in producing new warships but in rebuilding the nation’s industrial backbone. As America embarks on its most ambitious fleet expansion in decades, FibrX offers a critical enabling technology to ensure these ships are not just the largest ever built, but also the smartest, safest, versatile, transformable, and the most sustainable ships to sail the high seas. References (1) World Ports Organization, US Shipbuilding Faces Urgent Challenges (2025). (2) World Ports Organization, China Strengthens Lead in Global Shipbuilding for 2025. (3) 19FortyFive, China’s Navy Is Bigger (2025). (4) Congress.gov, FY2025 Defense Appropriations Summary. (5) CBO, Analysis of the Navy’s 2025 Shipbuilding Plan.

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3 steps to navigate the DoD’s hidden power structures There is no front door to the Department of Defense. Only a maze of stakeholders who don’t speak your language If you’re a startup trying to break into defense, you already know the feeling: • You demo • They’re impressed • Then… nothing That’s because most founders approach the DoD like a single buyer. But Giles W. - retired Marine and former AWS mission lead - says federal traction happens when you solve for three separate power centers at once. Here’s how he breaks it down for early-stage teams: __________________________ Step #1: Earn trust at the edge This is the warfighter (the end-user who actually needs your tech) They’re the ones facing the problem you solve. But showing up with a sharp demo isn’t enough. You have to: • Solve an actual operational pain • Prove usability in the field • Get them to advocate up the chain Without their support, your tech’s just another line in a white paper. __________________________ Step # 2: Speak procurement to the PM Program Managers are the system owners. They hold the purse strings and care about: • Compliance • Integration • Risk Giles calls this the most overlooked gatekeeper. Founders win by mapping capabilities directly to what the PM’s protecting—not just what the warfighter wants. Your job is to make their job easier. __________________________ Step # 3: Align to a senior leader’s mission (without wasting their time) Senior leaders aren’t blocking you, they’re buried. “Clobbered with time,” as Giles puts it. You need to: • Show clear strategic fit • Help them visualize outcomes • Never over-explain This is where mission relevance, timing, and optics meet. __________________________ Most founders sell to the DoD like it’s one person. It’s not. It’s a three-headed buyer. And you only break in when you earn the trust of all three. That’s how Giles now helps pre-Series A companies survive federal. This is just the map outline. Giles walks you through the terrain. Listen to the full episode of The Amplified CEO https://lnkd.in/ea2sS8w5

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The Hidden Cost of SAM.gov Data Extraction With the transition away from direct FPDS access, federal procurement data is now primarily accessed through SAM.gov. On paper, the data is still available. In practice, extracting useful intelligence from SAM.gov can be surprisingly time-consuming. For many government contractors and consultants, the workflow looks something like this: - Navigate the SAM.gov search interface - Run multiple queries to locate the relevant data - Export large datasets - Clean and structure the data manually - Combine files across agencies or time periods - Analyze the results This process can easily consume hours or even days of analyst time. And that’s before the data is turned into meaningful insight. As organizations begin to feel this friction, some vendors are responding by offering training programs to help teams learn how to use SAM.gov more effectively. Training may help people navigate the system more efficiently. But it doesn’t eliminate the underlying problem. Manual data extraction is still manual. At Q247.ai, our BDx Federal SaaS platform addresses the issue from a different angle. Instead of training users to work around the complexity of SAM.gov, BDx automates the extraction process and delivers structured procurement data that is immediately usable! When combined with Q247.ai analytics, this data can power: • agency spending analysis • contract trend identification • competitive intelligence • opportunity discovery In other words, the value isn’t just in accessing the data. The value is in transforming raw procurement data into actionable intelligence. As the federal market becomes more data-driven, organizations that automate this pipeline will have a significant advantage. Schedule your demo today at www.Q247.ai so you can fill your funnel with relevant opportunities.

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Most GovCon companies don't lose on capability. They lose on timing. The pattern is almost always the same. Win the contract, then invest in the product. Get the product stable, then start marketing. Build the pipeline, then figure out what to sell. It feels disciplined. It's actually just slow. By the time each track is ready to hand off to the next, the opportunity has already shaped itself around someone else. The incumbent renewed. The budget got reprogrammed. The program office stopped returning calls. Here's what I've seen work instead. BD pursuing live opportunities while engineering is hardening the platform. Marketing building market presence and credibility before there's a contract to point to. Sales developing relationships in programs you haven't won yet — and may not win for 18 months. These tracks don't wait for each other. They inform each other. The objection I hear most from technical founders is "we don't have the resources to run all of this at once." That's a real constraint. But serializing doesn't conserve resources. It just redistributes the risk onto your timeline and in GovCon, timeline is the one thing you can't recover. At that point, sequential GTM isn't a strategy. It's just a slower way to watch someone else win. What's the track most technical founders underinvest in first, and why is it almost always marketing?

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NASA Engineer on agile in DoD: “I’ve worked at NASA and now on a complex DoD system-of-systems program... I’ve seen some programs swing so hard away from process that ‘agile’ just means doing whatever the customer wants, whenever they want it. That leads to constant scope changes and chaos. How do you navigate that?” One of the best questions from our recent webinar came from someone who’s worked across both NASA and DoD programs. 100% agree with the problem. Agile is one of the most misunderstood terms in engineering. People throw it around too loosely. Too often, it’s interpreted as: - “Just break the Gantt chart into sprints” - “No plan, just build” - “Everyone’s in charge, all the time” That’s not agility. That’s drift. What actually matters is how you burn down risk and deliver outcomes. Implementation—the guardrails—is everything. The best teams: 1. Anchor to clear top-level goals 2. Work bottom-up to figure out what they can build, fast 3. Use just enough process to move quickly and stay aligned Call it structured iteration. Call it outcome-driven engineering. Whatever the name, it’s not about rejecting process. It’s about using it intentionally . The real job is to give teams the autonomy to build creatively, and the structure to stay aligned. That’s what responsible engineering looks like. Whether the execution looks agile, waterfall, or somewhere in between.

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SOCOM just asked for AI that reasons like a human—responses due January 12. Most primes still aren't ready for what that actually means. This isn't your typical automation RFI. SOCOM wants agentic AI. Systems that perceive, reason, and act independently. Not rule-based bots following scripts. The April demo at Avon Park will separate real capabilities from PowerPoint promises. What they're actually asking for: • Multimodal perception (visual, audio, text) • Human-like decision making • Integration with existing SOF systems • Autonomous mission support • Collaborative human-AI teaming The use cases span everything from cybersecurity to mission planning. But here's the challenge: Most defense contractors are still building deterministic systems. They're not ready for AI that adapts and learns in real-time. The SWaP-C requirements make it even harder. Low size, weight, power, and compute? Good luck. This RFI signals a major shift. Special operations wants AI teammates, not just tools. The companies that crack this will reshape how commandos operate in complex environments. Three weeks to respond. The clock is ticking. Which defense tech companies do you think are closest to delivering true agentic AI? #DefenseTech #AI #SpecialOperations 𝗦𝗼𝘂𝗿𝗰𝗲꞉ https://lnkd.in/ggHu77dv

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I've started producing my documents as LaTeX converted PDFs again. Why? Because I use friction as a quality filter. When people can't just scatter comments in the margins of a Word document, they have to decide whether their feedback matters enough to actually write it down separately. You'd be amazed how much "feedback" doesn't survive that threshold. This is also the reason why I tell people to "own their edits" instead of adding comments. You send a document for review. What you're asking is "does this hold together, did I miss something, is the logic sound." What arrives back is someone who read the executive summary and maybe skimmed section three, now proposing to restructure the entire concept, a different document wearing yours as a disguise. And that's where it gets genuinely dangerous, because a well-structured document is a chain of reasoning. Each section builds on the previous one. The conclusions depend on the analysis, which depends on the framing, which depends on the problem statement. When someone who engaged with 20% of that chain starts pulling at the foundations, they're removing load-bearing walls because they don't like the paint color. For some reason I cannot understand authors let this happen. "Thank you for your valuable input" culture has trained us to treat every comment as equally valid, and they're simply not. Some feedback improves the work. Some is someone trying to redirect your document toward the document they wish they'd written themselves. Learning to tell the difference — and fighting for your structure when it matters — is a skill most people never develop. So yes, LaTeX Project and Adobe PDFs. Not because I'm stuck in the nineties. Because when giving feedback requires actual effort, the only feedback that arrives is the kind worth reading. Friction is the filter that makes collaboration worth having. #DocumentManagement #Leadership #DigitalTransformation #OrganizationalDysfunction

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Nobody wants to do enterprise architecture but everyone needs enterprise architecture. What services are you delivering for which audience? Which processes are required to make that delivery happen? Then start to think about necessary personnel and technology.

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If your revenue or core workflows are tied to AI/ML, you need a specialist... An AI/ML engineer is different as they don't feed dashboards, they power models. This is for the orgs who cross the chasm I mentioned yesterday. This is relatively new. Over the past 15 years we've seen a shift. Notebook-only workflows replaced by full blown AI/ML data engineers. They don't just help to build models. They ensure models run continuously and reliably. They form the foundation of production-grade AI products. Most companies hire for this role prematurely and try to cheat their way up the data maturity ladder to do some sweet ML and AI work. But the biggest differentiator is knowing how to tie AI directly to revenue and core business workflows. You are going to like this role if you enjoy: - Working with multimedia data - Building complex features and feature stores - Owning data versioning freshness, and consistency - Managing the lifecycle of training and inference pipelines The most underrated skill for AI/ML engineers is being able to architect solutions that meet the business problem's availability and accuracy needs. Do you prefer data work focused on numbers or multimedia data?

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Really appreciated this post — such a thoughtful take on what agility actually means.   “Agile” gets used as shorthand for speed—but without clear goals or structure, speed just becomes scatter.   When I join a team, I focus on: ➡️ What are we trying to achieve? ➡️ What’s blocking us? ➡️ How do we build a system that helps us move forward together?   Agile, waterfall, hybrid—it doesn’t matter what you call it.   What matters is clarity, collaboration, and process that enables creativity and progress.   #programmanagement #alignment #agile #operations #productdevelopment

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