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Shann³
@shannholmberg
I cover AI marketing & growth. Sharing every framework as I build it. Founder @espressioai, @lunarstrategy
加入 November 2021
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how external research becomes part of your marketing agents' knowledge when an agent researches competitors, customer conversations or formats for a campaign, some of what it finds will be useful again a recurring customer objection might change how you explain your offer and this week's trending format might only be relevant for the social posts you're creating now part of context management is deciding what to fetch for the current project and what your agents should keep using across future campaigns 1. separate company context from campaign work your company brain holds the context you reuse across campaigns, like what you sell, who your customers are, your voice and the decisions you've agreed to keep each campaign has its own campaign brain, a folder for its goal, brief, research, decisions and all the working files, including ideas, drafts, documents and results it also links to designs and other work kept in external tools, so the agent can find everything connected to that campaign agents use the campaign brain alongside the relevant company files while working external research starts in the campaign brain. when you and the agent identify something worth using across future campaigns, you add that finding to the company brain with its source and your reasoning 2. work out what you need to learn start with your campaign idea and goal / objective, then give the agent access to the context you have have it read relevant previous campaigns and ask about your experience before planning the research. you may have already tested an approach, ruled out an audience or learned something that never made it into a file 3. fetch research that helps with those decisions depending on the campaign, that could include: > competitors' current pricing, offers and positioning > how others approached similar campaigns and launches > trends and formats on the channel you're publishing to > comparable landing pages, ads, thumbnails and hooks > customer questions and objections in comments, reviews and relevant discussions > search results and ai answers for the questions your customers are asking > creators and potential partners for the campaign > seasonal moments and buying triggers, like hiring or funding keep the channel, audience and date attached to each finding. a format getting attention on x gives you something to investigate for x, with separate research needed for linkedin 4. save the research with the campaign use campaigns//research/ for the material collected for that project keep the original sources, then have the agent write the relevant findings into research/distilled. md with links back to the evidence include when the research was collected, why each finding matters and anything that still needs checking references. md links to this research alongside the company files, performance data and design references needed for the campaign large collections can stay in the research files or database. have the agent search and retrieve the relevant material as it works through each task 5. bring your experience into the decisions when research affects the campaign direction, have the agent explain its recommendation and ask for your context before proceeding you might recognize an objection from customers you don't serve, or know that a popular format previously brought in the wrong audience work through that together and save the agreed decision with its reasoning in the campaign brain. anything still waiting on your judgment goes into the sign-off queue this applies throughout the campaign, including changes made while creating and reviewing the assets 6. add lasting lessons to the company brain once a finding repeats, has support from your own results or becomes a decision you've signed off on, review whether future campaigns should use it > recurring customer phrases and objections go into customer. md > competitor findings that affect your positioning go into competitors. md > formats that performed well for you go into formats. md, with approved work in examples/ > decisions you want future campaigns to follow go into rulings. md, including why you made them keep the source, date and conditions with each addition. a format that worked for a particular offer and audience should carry that context into the next campaign
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context management is one of the core skills for a marketing engineer when you give an agent a campaign to work on, it needs to understand the business, use what you've learned from previous campaigns and follow your taste in the work it creates your second brain gives it the company knowledge, but you also need to connect it to performance data and a brand book you can work in together tldr > company brain = helps the agent understand your business and the work you're doing > warehouse = lets the agent measure performance and learn from results > brand book = guides the agent's design choices using your style and feedback keep references. md in the project so whichever harness you're using can find the relevant files, query the data and open the designs with your feedback 1. connect your context sources with references. md your harness is the software that runs the agent, like cursor, grok bot, claude code or hermes references. md holds links and instructions for finding context. the company files stay in the brain, performance data in the warehouse and designs in the brand book before making a decision, the agent should ask for your relevant context and experience, including what you've already tried, what you learned and anything that hasn't been written down yet for a landing page + social posts, the agent needs to: > work with you to define the campaign brief, starting from your idea, goal and experience > read company knowledge, previous campaigns, decisions and lessons from the brain > query previous campaign performance in the warehouse > open the brand book and approved designs, including your feedback > bring the evidence back to you and work through decisions together save the agreed brief and the reasoning behind your decisions in the campaign brain as the work progresses 2. keep company knowledge and decisions in the brain use markdown in git, with github as the shared place to keep it. the agent reads the files relevant to the job your company brain holds context that should remain useful across campaigns > what you sell, who buys and why > positioning, supported claims and exclusions > voice-dna. md, hooks. md and approved work > dated decisions and permissions to edit, spend or publish your campaign brain holds the context for the work in progress > this campaign's goal, audience, offer and constraints > decisions you've already made and why > approved versions, rejected drafts and your edit notes keep performance data in the warehouse. the visual/ folder holds links to design. md and the live brand file 3. keep performance in the warehouse use postgres or another sql database. define what each row represents, such as one asset in one campaign on one date keep the facts you use to make marketing decisions > spend, impressions, clicks, leads and conversions > content results, like saves, replies or watch time > lead source and stage in your customer relationship management system > experiments, dates and what you stopped running keep definitions beside the numbers. define what counts as a lead or conversion, which reporting window to use and how much the data can lag use shared identifiers like campaign_id and asset_id to connect records across sources recurring jobs pull the data on a schedule. the warehouse connects the records and calculates totals with sql, the language used to query the database your agent queries the warehouse for the results it needs, instead of pulling bulk history from each platform into its context for the landing page job, it can query the last similar campaign by asset over the last 28 days, using the same conversion definition save your interpretation in the campaign brain with a link to the query. keep the performance history in the warehouse 4. keep your design rules and visual feedback in the brand book this needs both written rules and a live design file you can work in together design. md gives the agent instructions it can read before creating anything > typefaces, sizes and when to use them > colors, contrast and logo placement > layouts, safe zones and formats for each channel > do / don't examples with the reason beside them > what it can create and what it should only adapt > links to the paper or figma file and the pages to open write your brand guidelines in design. md and link each guideline to an example in paper or figma. include your feedback on why a design works or what needs to change paper and figma mcp give the agent access to the live design file. mcp is the connection that lets it use the design tool keep your brand book, moodboard and approved work there > add a note explaining what you like about each reference > keep approved ads, landing pages and social designs > keep rejected versions with your comments on the frames > leave feedback next to the work you're discussing design. md explains the requirements. the live file lets the agent inspect examples, create designs and work alongside you as you review them 5. use all three context sources, and save what decisions and changes for the landing page + social posts, the agent reads the relevant company files and campaign brief, queries previous performance, then reads design. md and opens the brand page with approved examples work through the direction together before drafting copy and frames in paper or figma. send the work to your sign-off queue for review after approval, save the copy and the reason for your edits in a campaign folder. keep the approved frames and design feedback in the brand file after launch, results go to data warehouse and your interpretation goes in the company / campaign brain the models are interchangeable, but your company knowledge, performance history and design judgment carry into the next campaign you´ll be working on
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