Add styled landing page intros to AI and context engine docs#3558
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Adds tagline, three clickable cards, "What is X?" and "Why use X?" sections with Redis-palette styling to the Redis for AI, Context Engine, Agent Memory, LangCache, Context Retriever, Data Integration, and Feature Form index pages. Also renames "Agent Memory Server" to "Agent Memory" throughout. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Just a few suggestions but otherwise LGTM - good idea to make them all look consistent like this.
| {{< image-card image="images/ai-LLM-memory.svg" alt="Use cases icon" title="API and SDK Examples — See real-world usage patterns with session events and long-term memory" url="/develop/ai/context-engine/agent-memory/api-examples" >}} | ||
| {{< image-card image="images/ai-brain-2.svg" alt="Python SDK icon" title="Python SDK — Easy integration with tool abstractions for OpenAI and Anthropic" url="/develop/ai/context-engine/agent-memory/api-examples" >}} |
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These two tiles point to the same page. Also, it doesn't really contain any Python SDK examples (although it has a link to the PyPI page where there are some examples). Maybe use a different topic for the card or link directly to the PyPI page? Then again, maybe this is an indication that we do need some Python examples on redis.io.
| <ul class="space-y-1 text-redis-pen-600"> | ||
| <li>Agents reliably follow defined data paths instead of guessing at SQL</li> | ||
| <li>Live, structured context from your business data at every agent step</li> | ||
| <li>No tool zoo sprawl — one model definition, consistent tool surface</li> |
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Although the page intentionally has a slight marketing feel to it, I think "tool zoo sprawl" is a bit flowery! Maybe something like:
| <li>No tool zoo sprawl — one model definition, consistent tool surface</li> | |
| <li>Minimal tool set and single model definition keep things simple</li> |
Feel free to ignore this if "tool zoo sprawl" is in widespread use and it's just me who has never heard of it :-)
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| Stream live business data into Redis so agents always work with accurate, up-to-date information. | ||
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| Redis Data Integration (RDI) keeps your Redis Cloud database in sync with your existing relational databases using change data capture. Agents query Redis at full speed without ever touching your production databases directly. |
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Link might be helpful for people seeing this stuff for the first time, and defining the abbreviation is appropriate because it gets used later in the page. Also, "touching" might be a bit misleading since you do still have to write to the production databases.
| Redis Data Integration (RDI) keeps your Redis Cloud database in sync with your existing relational databases using change data capture. Agents query Redis at full speed without ever touching your production databases directly. | |
| Redis Data Integration (RDI) keeps your Redis Cloud database in sync with your existing relational databases using [Change data capture](https://en.wikipedia.org/wiki/Change_data_capture) (CDC). Agents query Redis at full speed without ever reading from your production databases directly. |
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| RDI performs an initial full sync, then captures every subsequent `INSERT`, `UPDATE`, and `DELETE` and applies them to Redis within seconds. See the [RDI quick start]({{< relref "/operate/rc/rdi/quick-start" >}}) to get up and running with a live PostgreSQL source. | ||
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The stuff that follows is existing text but it seems to repeat what is said in the new intro. Might be useful to do a quick tidy-up on the rest of the page to avoid redundant info.
| See the full [LangCache API and SDK examples]({{< relref "/develop/ai/context-engine/langcache/api-examples" >}}) for more. | ||
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| Redis LangCache is a fully-managed semantic caching service that reduces large language model (LLM) costs and improves response times for AI applications. | ||
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Another situation where the following text looks quite similar to what's already been said in some places.
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| Redis Feature Form helps teams define, manage, materialize, and serve machine learning features while keeping existing data systems in place. In the documented workflow, Redis acts as the low-latency online store for feature serving. |
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Not part of the PR, but maybe just remove this line now?
| Redis Feature Form helps teams define, manage, materialize, and serve machine learning features while keeping existing data systems in place. In the documented workflow, Redis acts as the low-latency online store for feature serving. |
| <div class="p-5 border border-redis-pen-300 rounded-lg"> | ||
| <h3 class="text-redis-ink-900 font-semibold mb-3">For developers</h3> | ||
| <ul class="space-y-1 text-redis-pen-600"> | ||
| <li>Python, JavaScript, Java, Go, and .NET client libraries</li> |
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PHP too, surprisingly :-) Also, maybe best to make it clear that these clients support search specifically (I think only Python/JS support the Iris stuff?)
| <li>Python, JavaScript, Java, Go, and .NET client libraries</li> | |
| <li>Redis Search available in Python, JavaScript, Java, Go, .NET, and PHP client libraries</li> |
- Fix duplicate card link in Agent Memory (card 3 now points to PyPI) - Add CDC hyperlink and change "touching" to "querying" in Data Integration - Add PHP to client library list and clarify search scope in develop/ai - Remove redundant old intro paragraphs in LangCache and Data Integration - Remove duplicate Deploy link in Feature Form - Remove unsupported MCP and LiteLLM claims from Agent Memory - Replace invented ctxctl command syntax with accurate description - Replace undocumented RDI YAML with link to quick start Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Adds tagline, three clickable cards, "What is X?" and "Why use X?" sections with Redis-palette styling to the Redis for AI, Context Engine, Agent Memory, LangCache, Context Retriever, Data Integration, and Feature Form index pages.
Note
Low Risk
Documentation-only Hugo markdown and marketing copy on index pages; no runtime, security, or API behavior changes.
Overview
Adds a shared landing-page pattern to seven Hugo index pages under
develop/ai: opening taglines, What is / Why use sections with Redis palette styling (text-redis-*, bordered two-column grids), red bullet lists, and threeimage-cardnavigation grids per page (where the page already had cards, new cards are added for Context Engine services).Redis for AI and search gains capability bullets (vector search, LangCache, agent memory, Context Retriever, live sync) plus audience split boxes before the existing Feature Form and agents sections.
Context Engine (Redis Iris) is restructured with Iris positioning, service cards, LangCache search/store Quick example JSON, and a shortened front-matter
description.LangCache, Agent Memory, Context Retriever, Data Integration, and Feature Form each replace or supplement terse intros with the same template, service-specific quick starts (REST JSON,
pip install, or config pointers), and deep links to operate/quick-start docs. Agent Memory renames the overview heading to Two-tier memory model and refers to the Agent Memory service instead of “Agent Memory Server.”No application code, APIs, or build logic change—only markdown content and layout classes.
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