Civic Technologies

Teams often reach for fine tuning because it feels like the obvious next step. The model seems weak. Performance drifts. Results stall. So they retrain. And they wait. But the real bottleneck usually sits upstream. Inputs wander. Context sprawls. Tools drift. The model guesses. That is where performance breaks. Prompt plumbing changes this. It reshapes the flow around the model so the model can focus on the part only it can do. It gives teams cleaner inputs, tighter context, predictable structure and faster iteration. The gains show up quickly because the system carries the clarity the model needs. This is the shift we explore in our latest post. Read the full post here: https://lnkd.in/gBkSdwCD #LLM #aiworkflows

Using holiday downtime to level up? Don’t miss our last workshop of the year — happening tomorrow. Jump into 2026 with 4 AI workflows under your belt. Your team will thank you for this-> https://lnkd.in/ghj-SgVj

If you’ve ever wondered what it takes to build what you used to buy in this new world of AI agents, this podcast is for you. Thank you to Phil Gamache and the Humans of Martech for hosting our own VP of Operations, Anna Aubuchon.

Most teams feel the moment when data hints at a story but refuses to land. That happens when analytics, storage and reporting drift apart. We built Civic Nexus to help restore that thread. It connects PostHog, Google Analytics, AWS Billing, Redshift and MongoDB so behavior, acquisition, cost and performance reinforce each other instead of competing for attention. You ask questions once. You get answers that match. You move with more confidence. If your stack feels noisy instead of clear, this will help. Read the full post here: https://lnkd.in/gzYBVhk4 #dataanalytics #marketingtech

Shaw Walters, founder of ElizaOS

We’ve watched AI agents stumble in ways that have nothing to do with intelligence. They lose the thread the moment workflows stretch across steps, tools, or decisions. We’ve seen agents read entire websites and flag irrelevant compliance issues. We’ve seen them forget earlier conclusions buried inside complex contracts. We’ve seen support agents confidently repeat fixes customers completed weeks earlier. Different teams. Same failure mode. Once context gets tangled, the system can’t stay coherent. The real issue is structural. Agents carry no persistent memory and inherit noise faster than they inherit signal. Larger windows don’t solve that. Retrieval tricks don’t solve it. Coherence comes from architecture, not scale. We break down why this matters for production systems in our latest post. Read the full post here https://lnkd.in/gQDrPj7e #AI #EnterpriseAI

Missed our podcast? You’re in luck! A new episode of Agents in Context just dropped. Mitchell Amador (CEO, Immunefi) joins us to talk: 🦠 Next-gen ransomware 🤖 Spear-phishing autonomous agents 💰 Why defenders need new incentives Watch now → https://lnkd.in/gMCAmdSn

Support teams don’t struggle because they lack skill. They struggle because work scatters across too many places before anyone notices. That gap is what Civic Nexus closes. We brought Intercom, Gmail, Notion, Linear and Slack into a single support stack so conversations keep moving and every teammate sees the full picture. It feels steady and personal because nothing slips away while people switch tools or rebuild context. The post walks through how real teams use Civic Nexus to turn chats into tickets, summarize inboxes, surface urgent needs and update documentation without breaking stride. Read the full post here: https://lnkd.in/gZjmYwRK #support #customersupport

Quiet days around the holidays are the perfect time to upgrade your skills. Take this time to learn practical AI workflows that removes busywork from your job so you can return to work sharper, faster, and ready to impress. We’ll show you how: 💻 automatically monitor your website ⏰ prep for meetings in seconds 🤝 uncover collaboration opportunities 📈 analyze public sentiment across real conversations. Reserve your spot here -> https://lnkd.in/ghj-SgVj

Most AI programs fail for a simple reason. Teams chase moonshots instead of fixing the work that slows them down every day. Wharton surveyed more than 800 enterprise leaders. Nearly three quarters already see positive AI returns. The surprise is where that value comes from. Not massive, futuristic initiatives. Instead, the gains show up in the repeatable tasks teams handle constantly. Meeting notes. Data analysis. Document handling. The companies pulling ahead build small wins quickly. They reduce friction. They make it easy for teams to ship AI features without rebuilding security, auth and integrations every time. The rest stay in pilot mode waiting for a perfect use case. If your teams rely on manual plumbing, you are already behind. Start learning about supporting more efficient custom AI workflows: https://lnkd.in/gPPGszhv