6 AI agent terms you need to know in 2026: (Most developers still confuse #1 and #2) 𝟭. 𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 (𝗠𝗖𝗣) Think of it as "USB-C for AI" - a universal standard that…

376174331 viral

AI Agent Engineering4 days ago

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Why do most RAG systems fail when you ask them anything complex? Most linear pipelines lack the reasoning required for depth. → 𝗡𝗮𝗶𝘃𝗲 𝗥𝗔𝗚 follows a fixed path of retrieval and generation. If…

166181714 viral

Generative AI6 days ago

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Is your RAG pipeline failing because of your data, or because of your queries? Most developers optimize their vector databases. But smart developers optimize their queries first. These 4 techniqu…

13851912 viral

LLM Engineering13 days ago

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AI memory systems don't fail because they forget. They actually fail because they remember everything. If you've ever used an agent that repeats your own preferences back to you, or worse, ignores t…

78635 viral

AI Infrastructure12 days ago

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Developer marketeers watching the ‘safe’ corporate AI-generated post they were forced to publish die in the feed like 🤡

23001 viral

AI Content Marketing18 days ago

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Topics & Content Focus

Primary Topics

Agentic AI architecture for production systems (single-agent vs multi-agent, skills, tool protocols)RAG reliability engineering (agentic search, query agents, query-first optimization)AI memory as infrastructure (governance, maintenance, lifecycle controls)

Secondary Themes

Developer enablement content (glossaries, frameworks, checklists that reduce implementation ambiguity)Product-integrated education (Weaviate-centric patterns, integration friction reduction)Internal enterprise use cases for LLM apps (legal/contract analysis workflows)

Industry Focus

Developer-focused B2B AI infrastructure / vector database ecosystemEnterprise LLM applications (RAG + agents) with a platform/product lens

Content Categories

Technical explainers (concept-to-implementation translation)Contrarian diagnostics (why systems fail, root-cause framing)Framework/list posts (numbered terms, techniques, architectures)Mini case studies (internal team validation, build-time claims)Brand voice/meme commentary (rare, culture critique)

Performance Insights

181.8%

Avg Engagement Rate

STABLE

Performance Trend

Best Performing Topics

Agent term glossaries and definitional clarity (protocols, skills, architectures)Agentic RAG + query agents (autonomous routing, search strategy reasoning)Query-first optimization frameworks (decomposition, routing, transformation)

Virality Signals

Shareable, screenshot-friendly frameworks (numbered techniques/terms) correlate with higher sharesNovel vocabulary + standard-setting metaphors (e.g., protocol-as-USB-C) increase repost potentialClear enemy/foil framing (naive vs agentic, linear vs reasoning) improves “forward-to-team” behaviorResource links packaged as implementation pathways (blog/ebook) reinforce distribution beyond likes

Structure & Quality

260

Avg Length (Words)

HIGH

Depth Level

ADVANCED

Expertise Level

0.82/10

Uniqueness Score

Common Hooks

Authority glossary hook ("X terms you need to know") with a curiosity gap ("Most people confuse #1 and #2")Failure-mode hook ("Why do most systems fail when...") that reframes the real causeContrarian comparison ("Most developers optimize A. Smart developers optimize B first.")Paradox opener ("They don’t fail because they forget—they fail because they remember everything")

Common Endings

Direct question to invite replies ("Which am I missing?")Resource drop (blog/ebook link) as the next stepSoft product positioning ("At Weaviate, we're building...")Invite to preview / signup (early-access CTA)

Value Delivery Methods

Turns emerging agent concepts into operational definitions and system componentsDiagnoses failure modes and proposes upstream fixes (query strategy, memory governance)Provides implementation-shaped checklists that map to real pipelines (routing, reranking, synthesis)Anchors abstractions with credible applied validation (legal team contract workflows)

Formatting Style

Heavy scannability: short paragraphs, frequent line breaksNumbered frameworks (1–6, 1–4) and labeled sub-sectionsBold/typographic emphasis for key nouns and headingsChecklist-style bullets with clear verbs (analyzes, decides, reranks, synthesizes)Occasional meme-style one-liner (low-frequency format experiment)

Audience & Tone

YES

Question Usage

0.3%

Response Rate

Detected Tone

Technical authority with educator intentBuilder-first, systems-thinking orientationSmart-casual contrarian (calls out common mistakes without being hostile)Product-led but value-forward (teaches first, then points to Weaviate)semi-formalsecond-person

Interaction Style

Prompted discussion via end-of-post questionsPeer-level builder talk (assumes technical fluency, invites refinement/edge cases)Resource-driven engagement (comments as follow-up questions to implement links/frameworks)

Community Building Signals

Positions the creator as a translator between research concepts and production engineeringBuilds a learning loop around owned assets (blogs, ebook) and product roadmap previewsCreates shared language for the community (standardized terms, roles, architectures)

Femke Plantinga

Performance Overview

Top Posts by Engagement

Posting Patterns & Frequency

Best Performing Days

Best Performing Times To Post

Topics & Content Focus

Primary Topics

Secondary Themes

Industry Focus

Content Categories

Performance Insights

Best Performing Topics

Virality Signals

Structure & Quality

Common Hooks

Common Endings

Value Delivery Methods

Formatting Style

Audience & Tone

Detected Tone

Interaction Style

Community Building Signals

Writing Style Patterns

Content Strategy